Data Entry Quotes

Get It Done Fast, Cost Effective and With Professional Results to Outsource Your Medical Data Entry Functions

what is the expression which the age demands? the age demands no expression whatever. we have seen photographs of bereaved asian mothers. we are not interested in the agony of your fumbled organs. there is nothing you can show on your face that can match the horror of this time. do not even try. you will only hold yourself up to the scorn of those who have felt things deeply. we have seen newsreels of humans in the extremities of pain and dislocation. you are playing to people who have experienced a catastrophe. this should make you very quiet. speak the words, convey the data, step aside. everyone knows you are in pain. you cannot tell the audience everything you know about love in every line of love you speak. step aside and they will know what you know because you know it already. you have nothing to teach them. you are not more beautiful than they are. you are not wiser. do not shout at them. do not force a dry entry. that is bad sex. if you show the lines of your genitals, then deliver what you promise. and remember that people do not really want an acrobat in bed. what is our need? to be close to the natural man, to be close to the natural woman. do not pretend that you are a beloved singer with a vast loyal audience which has followed the ups and downs of your life to this very moment. the bombs, flame-throwers, and all the shit have destroyed more than just the trees and villages. they have also destroyed the stage. did you think that your profession would escape the general destruction? there is no more stage. there are no more footlights. you are among the people. then be modest. speak the words, convey the data, step aside. be by yourself. be in your own room. do not put yourself on. do not act out words. never act out words. never try to leave the floor when you talk about flying. never close your eyes and jerk your head to one side when you talk about death. do not fix your burning eyes on me when you speak about love. if you want to impress me when you speak about love put your hand in your pocket or under your dress and play with yourself. if ambition and the hunger for applause have driven you to speak about love you should learn how to do it without disgracing yourself or the material. this is an interior landscape. it is inside. it is private. respect the privacy of the material. these pieces were written in silence. the courage of the play is to speak them. the discipline of the play is not to violate them. let the audience feel your love of privacy even though there is no privacy. be good whores. the poem is not a slogan. it cannot advertise you. it cannot promote your reputation for sensitivity. you are students of discipline. do not act out the words. the words die when you act them out, they wither, and we are left with nothing but your ambition. the poem is nothing but information. it is the constitution of the inner country. if you declaim it and blow it up with noble intentions then you are no better than the politicians whom you despise. you are just someone waving a flag and making the cheapest kind of appeal to a kind of emotional patriotism. think of the words as science, not as art. they are a report. you are speaking before a meeting of the explorers' club of the national geographic society. these people know all the risks of mountain climbing. they honour you by taking this for granted. if you rub their faces in it that is an insult to their hospitality. do not work the audience for gasps ans sighs. if you are worthy of gasps and sighs it will not be from your appreciation of the event but from theirs. it will be in the statistics and not the trembling of the voice or the cutting of the air with your hands. it will be in the data and the quiet organization of your presence. avoid the flourish. do not be afraid to be weak. do not be ashamed to be tired. you look good when you're tired. you look like you could go on forever. now come into my arms. you are the image of my beauty.

Abracadabra," Roarke stated, and opened it. "Now that's more like it." Hunkered down beside him, Eve studied the neat stacks of cash. "This is how he stayed out of a cage so long. No credit, no e-transfers. Cash on the line. And a file box, loaded with discs and vids." "Best of all." Roarke reached in, took out a PPC. "His personal palm, very likely uninfected and chock-full of interesting data." "Let's load it up, get it in." She pulled out her memo book. "What're you doing?" "Logging the entry. I better not see any of that green stuff or those baubles go into your pockets, Ace." "Now I'm offended." He straightened, brushed at his shirt. "If I nipped anything, you can bet your ass you wouldn't see me do it.

Perhaps the best way to welcome women into churches is not to saddle them upon entry with an array of “shoulds” to add to their lists of commitments. Instead, women need to find a place of support that recognizes the value of their many hats and empowers them to live well into those roles. And right now, the data suggest women are not finding such a place at church.

The success of college towns and big cities is striking when you just look at the data. But I also delved more deeply to undertake a more sophisticated empirical analysis. Doing so showed that there was another variable that was a strong predictor of a person’s securing an entry in Wikipedia: the proportion of immigrants in your county of birth. The greater the percentage of foreign-born residents in an area, the higher the proportion of children born there who go on to notable success. (Take that, Donald Trump!) If two places have similar urban and college populations, the one with more immigrants will produce more prominent Americans. What

there was another variable that was a strong predictor of a person’s securing an entry in Wikipedia: the proportion of immigrants in your county of birth. The greater the percentage of foreign-born residents in an area, the higher the proportion of children born there who go on to notable success. (Take that, Donald Trump!)

In the mid-1990s, a new employee of Sun Microsystems in California kept disappearing from their database. Every time his details were entered, the system seemed to eat him whole; he would disappear without a trace. No one in HR could work out why poor Steve Null was database kryptonite. The staff in HR were entering the surname as “Null,” but they were blissfully unaware that, in a database, NULL represents a lack of data, so Steve became a non-entry. To computers, his name was Steve Zero or Steve McDoesNotExist. Apparently, it took a while to work out what was going on, as HR would happily reenter his details each time the issue was raised, never stopping to consider why the database was routinely removing him.

In fact, as these companies offered more and more (simply because they could), they found that demand actually followed supply. The act of vastly increasing choice seemed to unlock demand for that choice. Whether it was latent demand for niche goods that was already there or a creation of new demand, we don't yet know. But what we do know is that the companies for which we have the most complete data - netflix, Amazon, Rhapsody - sales of products not offered by their bricks-and-mortar competitors amounted to between a quarter and nearly half of total revenues - and that percentage is rising each year. in other words, the fastest-growing part of their businesses is sales of products that aren't available in traditional, physical retail stores at all. These infinite-shelf-space businesses have effectively learned a lesson in new math: A very, very big number (the products in the Tail) multiplied by a relatives small number (the sales of each) is still equal to a very, very big number. And, again, that very, very big number is only getting bigger. What's more, these millions of fringe sales are an efficient, cost-effective business. With no shelf space to pay for - and in the case of purely digital services like iTunes, no manufacturing costs and hardly any distribution fees - a niche product sold is just another sale, with the same (or better) margins as a hit. For the first time in history, hits and niches are on equal economic footing, both just entries in a database called up on demand, both equally worthy of being carried. Suddenly, popularity no longer has a monopoly on profitability.

Distraction leaches the authenticity out of our communications. When we are not emotionally present, we are gliding over the surface of our interactions and we never tangle in the depths where the nuances of our skills are tested and refined. A medical professor describes the easy familiarity with which her digital-native resident students master medical electronic records—but is troubled by the fact that they enter data with their eyes focused on their digital devices, not on the patient in the room with them. Preoccupation with technology acts as a screen between the student and the patient’s real emotion, real fear, and real concern. It may also prevent these residents from noticing physical symptoms that the patient fails to mention. The easy busyness of medical record entry is a way to sidestep the more challenging dynamics of human connection. But experienced physicians know that interpersonal skills are essential to mastering the art and science of medical diagnosis.

Every entry, whether revised or reviewed, goes through multiple editing passes. The definer starts the job, then it’s passed to a copy editor who cleans up the definer’s work, then to a bunch of specialty editors: cross-reference editors, who make sure the definer hasn’t used any word in the entry that isn’t entered in that dictionary; etymologists, to review or write the word history; dating editors, who research and add the dates of first written use; pronunciation editors, who handle all the pronunciations in the book. Then eventually it’s back to a copy editor (usually a different one from the first round, just to be safe), who will make any additional changes to the entry that cross-reference turned up, then to the final reader, who is, as the name suggests, the last person who can make editorial changes to the entry, and then off to the proofreader (who ends up, again, being a different editor from the definer and the two previous copy editors). After the proofreaders are done slogging through two thousand pages of four-point type, the production editors send it off to the printer or the data preparation folks, and then we get another set of dictionary pages (called page proofs) to proofread. This process happens continuously as we work through a dictionary, so a definer may be working on batches in C, cross-reference might be in W, etymology in T, dating and pronunciation in the second half of S, copy editors in P (first pass) and Q and R (second pass), while the final reader is closing out batches in N and O, proofreaders are working on M, and production has given the second set of page proofs to another set of proofreaders for the letter L. We all stagger our way through the alphabet until the last batch, which is inevitably somewhere near G, is closed. By the time a word is put in print either on the page or online, it’s generally been seen by a minimum of ten editors. Now consider that when it came to writing the Collegiate Dictionary, Eleventh Edition, we had a staff of about twenty editors working on it: twenty editors to review about 220,000 existing definitions, write about 10,000 new definitions, and make over 100,000 editorial changes (typos, new dates, revisions) for the new edition. Now remember that the 110,000-odd changes made were each reviewed about a dozen times and by a minimum of ten editors. The time given to us to complete the revision of the Tenth Edition into the Eleventh Edition so production could begin on the new book? Eighteen months.

market. Instead, we need to keep in mind that the representation is just a shortcut for presenting a lot of information, or even worse, a distortion of that information. Reliability bias People assume that something is accurate when it may not be. For example, market data that you use in your historical testing or that come to you live are often filled with errors. Unless you assume that errors can and do exist, you may make lots of mistakes in your trading and investing decisions. Lotto bias People want to control the market, and so they tend to focus on entry, where they can “force” the market to do a lot of things before they enter. Unfortunately, once they enter, the market is going to do what the market is going to do. And

From a nitty-gritty, practical standpoint, here is the drill that can get you there:   Loose Papers Pull out all miscellaneous scraps of paper, business cards, receipts, and so on that have crept into the crevices of your desk, clothing, and accessories. Put it all into your in-basket for processing.   Process Your Notes Review any journal entries, meeting notes, or miscellaneous notes scribbled on notebook paper. List action items, projects, waiting-fors, calendar events, and someday/ maybes, as appropriate. File any reference notes and materials. Stage your “Read/Review” material. Be ruthless with yourself, processing all notes and thoughts relative to interactions, projects, new initiatives, and input that have come your way since your last download, and purging those not needed.   Previous Calendar Data Review past calendar dates in detail for remaining action items, reference information, and so on, and transfer that data into the active system. Be able to archive your last week’s calendar with nothing left uncaptured.   Upcoming Calendar Look at future calendar events (long- and short-term). Capture actions about arrangements and preparations for any upcoming events.   Empty Your Head Put in writing (in appropriate categories) any new projects, action items, waiting-fors, someday/maybes, and so forth that you haven’t yet captured.   Review “Projects” (and Larger Outcome) Lists Evaluate the status of projects, goals, and outcomes one by one, ensuring that at least one current kick-start action for each is in your system.   Review “Next Actions” Lists Mark off completed actions. Review for reminders of further action steps to capture.   Review “Waiting For” List Record appropriate actions for any needed follow-up. Check off received items.   Review Any Relevant Checklists Is there anything you haven’t done that you need to do?   Review “Someday/Maybe” List Check for any projects that may have become active and transfer them to “Projects.” Delete items no longer of interest.   Review “Pending” and Support Files Browse through all work-in-progress support material to trigger new actions, completions, and waiting-fors.   Be Creative and Courageous Are there any new, wonderful, hare-brained, creative, thought-provoking, risk-taking ideas you can add to your system?

The difference in cost-efficiency was over a factor of four in favor of the low-end server. When looking for more recent data to update this section we realized that there are no competitive benchmarking entries that represent the high-end server design space. As we observed in 2009, the economics of the server space made that class of machines nearly obsolete in the marketplace today. The more interesting discussions today are between low-end server nodes and extremely low end (so-called Wimpy) servers,

Dimensions for Descriptive Context Dimensions provide the “who, what, where, when, why, and how” context surrounding a business process event. Dimension tables contain the descriptive attributes used by BI applications for filtering and grouping the facts. With the grain of a fact table firmly in mind, all the possible dimensions can be identified. Whenever possible, a dimension should be single valued when associated with a given fact row. Dimension tables are sometimes called the “soul” of the data warehouse because they contain the entry points and descriptive labels that enable the DW/BI system to be leveraged for business analysis. A disproportionate amount of effort is put into the data governance and development of dimension tables because they are the drivers of the user's BI experience. Chapter 1 DW/BI and Dimensional Modeling Primer Chapter 3 Retail Sales Chapter 11 Telecommunications Chapter 18 Dimensional Modeling Process and Tasks Chapter 19 ETL Subsystems and Techniques

Each business process is represented by a dimensional model that consists of a fact table containing the event's numeric measurements surrounded by a halo of dimension tables that contain the textual context that was true at the moment the event occurred. This characteristic star-like structure is often called a star join, a term dating back to the earliest days of relational databases. Figure 1.5 Fact and dimension tables in a dimensional model. The first thing to notice about the dimensional schema is its simplicity and symmetry. Obviously, business users benefit from the simplicity because the data is easier to understand and navigate. The charm of the design in Figure 1.5 is that it is highly recognizable to business users. We have observed literally hundreds of instances in which users immediately agree that the dimensional model is their business. Furthermore, the reduced number of tables and use of meaningful business descriptors make it easy to navigate and less likely that mistakes will occur. The simplicity of a dimensional model also has performance benefits. Database optimizers process these simple schemas with fewer joins more efficiently. A database engine can make strong assumptions about first constraining the heavily indexed dimension tables, and then attacking the fact table all at once with the Cartesian product of the dimension table keys satisfying the user's constraints. Amazingly, using this approach, the optimizer can evaluate arbitrary n-way joins to a fact table in a single pass through the fact table's index. Finally, dimensional models are gracefully extensible to accommodate change. The predictable framework of a dimensional model withstands unexpected changes in user behavior. Every dimension is equivalent; all dimensions are symmetrically-equal entry points into the fact table. The dimensional model has no built-in bias regarding expected query patterns. There are no preferences for the business questions asked this month versus the questions asked next month. You certainly don't want to adjust schemas if business users suggest new ways to analyze their business.

This shows that even a slight spatial or casual dependency between data entries or operations could kill scalability, so separation of data into independent shards and careful data modeling is extremely important for scalability.

The story of the conquest in Joshua does not accord, either in its general outlook or its specific details, with the archeological data (see “Archeology,” pp. 2124–36). These data suggest that instead of a violent entry into a populated land, the first Israelites settled a mostly empty part of the region, the central hill country. Archeology also contradicts the detailed stories of the conquest of the two cities, Jericho and Ai, which were apparently not inhabited during the Late Bronze Age.

My post-cruise sabbatical would spark the idea for my first book, Cheaper Than Therapy: How to Keep Life’s Small Problems from Becoming Big Ones – The Lesson of the Paper Clips. How? In my data entry job all I did for 20 hours a week was paper clip printouts of computer screens. For three years. I loved it.

We can instantly map the usage of the word 'raven' across the United States, in works of narrative poetry, written by men in their thirties. but only up to 1923. When it comes to the last century, save if new law affords entry, then the lawyer - dark-robed sentry - who is ever at our door, will yet whisper, "Nevermore!

Technically, a blockchain is simple. It’s an append-only ledger (using a data structure called a Merkle tree) — like an account book where you can only add new entries, not alter or remove old ones — and some mechanism to decide who adds the next entry. You can distribute copies of the ledger, and anyone receiving one can check they have a good copy. That’s it. That’s the whole thing.44* Blockchains are really simple — and when normal people find out what a blockchain actually is, they go: “What? That’s not magical at all. How do they get all of the nonsense I’ve read out of that?

Doing so showed that there was another variable that was a strong predictor of a person’s securing an entry in Wikipedia: the proportion of immigrants in your county of birth. The greater the percentage of foreign-born residents in an area, the higher the proportion of children born there who go on to notable success. Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are

This is the subject of an art work by the Brooklyn-based artist Andrew Norman Wilson called ScanOps. The project began in 2007, when Wilson was contracted by a video-production company to work on the Google campus. He noted sharp divisions between the workers; one group, known as ScanOps, were sequestered in their own building. These were data-entry workers, the people to whom those mysterious hands belonged. Wilson became intrigued by them, and began filming them walking to and from their ten-hour shifts in silence. He was able to capture a few minutes of footage before Google security busted him. In a letter to his boss explaining his motives, Wilson remarked that most of the ScanOps workers were people of color. He wrote, “I’m interested in issues of class, race and labor, and so out of general curiosity, I wanted to ask these workers about their jobs.” In short order, he was fired.

As a technology and an industry, AI naturally gravitates toward monopolies. Its reliance on data for improvement creates a self-perpetuating cycle: better products lead to more users, those users lead to more data, and that data leads to even better products, and thus more users and data. Once a company has jumped out to an early lead, this kind of ongoing repeating cycle can turn that lead into an insurmountable barrier to entry for other firms.

These are the four core functions of a platform: Audience building: Build a liquid marketplace by attracting a critical mass of consumers and producers. Matchmaking: Connect the right consumers with the right producers in order to facilitate transactions and interactions. Providing core tools and services: Build tools and services that support the core transaction by lowering transaction costs, removing barriers to entry, and making the platform more valuable over time through data. Creating rules and standards: Set guidelines that govern which behaviors are allowed and encouraged and which are forbidden or discouraged.

Novice traders believe that when they enter the trade, they should not do anything else but patiently wait for the price to hit their profit target or stop loss level. This is the opposite of what professional traders do. The professionals know that this is not enough. When you plan for the trade and enter a position, you have a minimum of information about the market and the validity of your idea. As the market moves after your entry, you will receive new price action and data about your initial trade idea: the price action of the stock is either supporting or not supporting your reasons for being in that trade. Therefore, you need to manage your open position.

FLT enables the corporate possibilities. We specialize in BPO services like medical billing, transcription service, call center service, data entry in India.

The online encyclopedia, Wikipedia, has entries that tend to change rather often and is biased toward the religion of secularism. Even so, they write: Typically a steep-walled, narrow gorge is inferred to represent slow persistent erosion. But because many of the geological formations of Canyon Lake Gorge are virtually indistinguishable from other formations which have been attributed to long term (slower) processes, the data collected from Canyon Lake Gorge lends further credence to the hypothesis that some of the most spectacular canyons on Earth may have been carved rapidly during ancient megaflood events.7 Notice that the religion of secular humanism still reigns supreme in this quote. The encyclopedia refuses to give the possibility of a global Flood (Noah’s Flood) being the triggering factor (as well as subsequent factors resulting from the Flood) for many of the great canyon’s formations. Instead they appeal to “megafloods.” But regardless, major floods and other catastrophes destroy the idea of millions of years and long ages.

Identify Your Strengths With Strengths Finder 2.0 One tool that can help you remember your achievements is the ‘Strengths Finder’ "assessment. The father of Strengths Psychology, Donald O. Clifton, Ph.D, along with Tom Rath and a team of scientists at The Gallup Organization, created StrengthsFinder. You can take this assessment by purchasing the Strengths Finder 2.0 book. The value of SF 2.0 is that it helps you understand your unique strengths. Once you have this knowledge, you can review past activities and understand what these strengths enabled you to do. Here’s what I mean, in the paragraphs below, I’ve listed some of the strengths identified by my Strengths Finder assessment and accomplishments where these strengths were used. “You can see repercussions more clearly than others can.” In a prior role, I witnessed products being implemented in the sales system at breakneck speed. While quick implementation seemed good, I knew speed increased the likelihood of revenue impacting errors. I conducted an audit and uncovered a misconfigured product. While the customer had paid for the product, the revenue had never been recognized. As a result of my work, we were able to add another $7.2 million that went straight to the bottom line. “You automatically pinpoint trends, notice problems, or identify opportunities many people overlook.” At my former employer, leadership did not audit certain product manager decisions. On my own initiative, I instituted an auditing process. This led to the discovery that one product manager’s decisions cost the company more than $5M. “Because of your strengths, you can reconfigure factual information or data in ways that reveal trends, raise issues, identify opportunities, or offer solutions.” In a former position, product managers were responsible for driving revenue, yet there was no revenue reporting at the product level. After researching the issue, I found a report used to process monthly journal entries which when reconfigured, provided product managers with monthly product revenue. “You entertain ideas about the best ways to…increase productivity.” A few years back, I was trained by the former Operations Manager when I took on that role. After examining the tasks, I found I could reduce the time to perform the role by 66%. As a result, I was able to tell my Director I could take on some of the responsibilities of the two managers she had to let go. “You entertain ideas about the best ways to…solve a problem.” About twenty years ago I worked for a division where legacy systems were being replaced by a new company-wide ERP system. When I discovered no one had budgeted for training in my department, I took it upon myself to identify how to extract the data my department needed to perform its role, documented those learnings and that became the basis for a two day training class. “Sorting through lots of information rarely intimidates you. You welcome the abundance of information. Like a detective, you sort through it and identify key pieces of evidence. Following these leads, you bring the big picture into view.” I am listing these strengths to help you see the value of taking the Strengths Finder Assessment.

The Library of Congress, with other partners, continues to work on a new bibliographic framework (BIBFRAME). This framework will be an open-storage format based on newer technology, such as XML. A framework is merely a holder of content, and a more open framework will allow for easier access to stored metadata. While resource description and access (RDA) is a movement to rewrite cataloging rules, BIBFRAME is a movement to develop a new storage medium. The new storage framework may still use RDA as a means of describing content metadata, but it will move storage away from MARC to a new format based on standardized non-library technology. This new framework will encompass several important characteristics. It will transition storage of library metadata to an open format that is accessible for use by external systems, using standard technology employed outside of libraries. This will allow for libraries to share metadata with each other and with the rest of the Semantic Web. The new framework will also allow for the storage of both old and new metadata formats so that libraries may move forward without reworking existing records. Finally, the new framework will make use of formal metadata structure, as the benefit of named metadata fields has more power for search and discovery than the simple keyword searching employed by much of the Internet. Library metadata will become more important once its organized fields of information can be accessed by any standard non-library system. Embracing a new storage format for bibliographic metadata is much like adoption of a new computer storage format, such as moving your data storage from CD-ROM to an external USB hard drive; the metadata that libraries have created for decades will not be lost but will be converted to a new, more accessible, storage format, sustaining access to the information. Although these benefits may be seen by some, it can be expected that there may be resistance to changes in format as well. It will be no small undertaking to define how libraries will move forward and to then provide means for libraries to transition to new formats. Whatever transitions may be adopted, it will be important that libraries not abandon a structured metadata entry form in lieu of complete keyword formatting.

In the end, I abandoned my new life, along with the people who had helped me to put it together, and I returned to the world of strange games and secret systems they had saved me from. The summer after I left the cult, everyone was initially pleased with my progress in adjusting to everyday living: I was set up in a flat in town with my oldest friend, working part-time doing data entry in a bank and all set to go back to Trinity in October and repeat the year I had lost. But I had never really taken to the temping which had controlled the days since my rescue, and in my idle moments I let my mind turn back to the dangerous questions and mysteries, to the vanished actors and intrigues that I had promised to forget for good.

Roomba, made headlines when the company’s CEO, Colin Angle, told Reuters about its data-based business strategy for the smart home, starting with a new revenue stream derived from selling floor plans of customers’ homes scraped from the machine’s new mapping capabilities. Angle indicated that iRobot could reach a deal to sell its maps to Google, Amazon, or Apple within the next two years. In preparation for this entry into surveillance competition, a camera, new sensors, and software had already been added to Roomba’s premier line, enabling new functions, including the ability to build a map while tracking its own location. The market had rewarded iRobot’s growth vision, sending the company’s stock price to $102 in June 2017 from just $35 a year earlier, translating into a market capitalization of $2.5 billion on revenues of $660 million.1 Privacy

Mobile phone apps – 2012 Before building a QuickBooks app, I decided to try iPhone and Android apps. This my first experience entering an app store. Unfortunately, the apps failed for many reasons: User base too small: There are millions of mobile phone users, but that does not translate to millions of users for your software. There is a subsection of a user base that matters most. Too many competitors: The app stores were oversaturated. There were over a million apps, literally. There was no way to stand out from the rest. My apps became me-too apps. The Intuit app stores were just getting started at the time and there were far fewer apps. Difficult to gain entry: I tried game development, and good games are expensive to produce. You need a soundtrack and graphic designers. The cost of making an exceptional game is outrageous. There was no way I could afford it. Failed to show value: Since most apps were free, users refused to pay me. I tried in-app purchases, but most users were uninterested. I learned that businesses were a better target because I could show them how to save time. Failed to solve a problem: In my eyes, app stores were the only way to advertise my game. I failed to tap into my potential user base. Businesses have a clear data entry problem that I can fix, but consumers were too difficult to sell to. Technical issues: I submitted one app to the Windows Marketplace, and it failed 15 times. I had to wait for Apple to publish updates to my app weekly. I learned that my next plugin must receive updates in a few hours, instead of a few days. Users simply cannot wait this long for an issue to get fixed. This was the most important lesson that I learned, and it inspired me to make a cloud-based system. Different devices:

In the mid-1990s, a new employee of Sun Microsystems in California kept disappearing from their database. Every time his details were entered, the system seemed to eat him whole; he would disappear without a trace. No one in HR could work out why poor Steve Null was database kryptonite. The staff in HR were entering the surname as “Null,” but they were blissfully unaware that, in a database, NULL represents a lack of data, so Steve became a non-entry. To computers, his name was Steve Zero or Steve McDoesNotExist. Apparently, it took a while to work out what was going on, as HR would happily reenter his details each time the issue was raised, never stopping to consider why the database was routinely removing him.

The ideas behind Bitcoin and blockchain technology give us a new starting point from which to address this problem. That’s because the question of who controls our data should stem first from a more fundamental question about who or what institutions we must trust in order to engage in commerce, obtain services, or participate in modern society. We see compelling arguments for a complete restructuring of the world’s data security paradigm. And it starts with thinking about how Internet users can start to directly trust each other, so as to avoid having to pour so much information into the centralized hubs that currently sit in the middle of their online relationships. Solving data security may first require a deliberate move from what we call the centralized trust model to one of decentralized trust. In an age when technology is supposed to be lowering the cost of entry, the outdated centralized trust-management system has proven expensive and restrictive (think about the 2 billion people in the world who are unbanked). It has also failed—spectacularly. Even though the world spent an estimated $75 billion on cybersecurity in 2015, according to estimates by Gartner, total annual losses from online fraud theft were running at $400 billion that year, said Inga Beale, CEO of British insurance market Lloyd’s of London. If you’re alarmed by that figure—and you ought to be—try this one on for size: $2.1 trillion. That’s the estimated fraud loss Juniper Research came up with after extrapolating from current trends into the even more digitally interconnected world projected for 2019. To put that figure in perspective, at current economic growth rates, it would represent more than 2.5 percent of total world GDP.

Consider one scenario that some envisage in an IoT world, where a self-driving car that needs to get somewhere in a hurry can make a small payment to another self-driving car to let it pass. As discussed, you’ll need a distributed trust system to verify the integrity of the transaction, which may involve a lot more information than just that of the money transfer before it can be processed—for example, you may need to know whether the overtaking car is certified as safe to drive at the faster speed, or whether one car’s software can be trusted not to infect the other with malware. These kinds of verifications, as well as that of the fund balance in the paying car’s wallet, could be run through a blockchain log to check the validity of each side’s claims, giving each the assurances they need without having to rely on some certifying central authority. The question, though, is: would this transaction be easily processed if it were based on a private blockchain? What are the chances, in a country of more than 230 million cars, that both vehicles would belong to the same closed network run by a group of permissioned validating computers? If they weren’t part of the same network, the payment couldn’t go through as the respective software would not be interoperable. Other car manufacturers might not want to use a permissioned verification system for which, say, GM, or Ford, is the gatekeeper. And if they instead formed a consortium of carmakers to run the system, would their collective control over this all-important data network create a barrier to entry for newer, startup carmakers? Would it effectively become a competition-killing oligopoly? A truly decentralized, permissionless system could be a way around this “walled-garden” problem of siloed technology. A decentralized, permissionless system means any device can participate in the network yet still give everyone confidence in the integrity of the data, of the devices, and of the value being transacted. A permissionless system would create a much more fluid, expansive Internet of Things network that’s not beholden to the say-so and fees of powerful gatekeepers.

Learning Plan Template Before Entry Find out whatever you can about the organization’s strategy, structure, performance, and people. Look for external assessments of the performance of the organization. You will learn how knowledgeable, fairly unbiased people view it. If you are a manager at a lower level, talk to people who deal with your new group as suppliers or customers. Find external observers who know the organization well, including former employees, recent retirees, and people who have transacted business with the organization. Ask these people open-ended questions about history, politics, and culture. Talk with your predecessor if possible. Talk to your new boss. As you begin to learn about the organization, write down your first impressions and eventually some hypotheses. Compile an initial set of questions to guide your structured inquiry after you arrive. Soon After Entry Review detailed operating plans, performance data, and personnel data. Meet one-on-one with your direct reports and ask them the questions you compiled. You will learn about convergent and divergent views and about your reports as people. Assess how things are going at key interfaces. You will hear how salespeople, purchasing agents, customer service representatives, and others perceive your organization’s dealings with external constituencies. You will also learn about problems they see that others do not. Test strategic alignment from the top down. Ask people at the top what the company’s vision and strategy are. Then see how far down into the organizational hierarchy those beliefs penetrate. You will learn how well the previous leader drove vision and strategy down through the organization. Test awareness of challenges and opportunities from the bottom up. Start by asking frontline people how they view the company’s challenges and opportunities. Then work your way up. You will learn how well the people at the top check the pulse of the organization. Update your questions and hypotheses. Meet with your boss to discuss your hypotheses and findings. By the End of the First Month Gather your team to feed back to them your preliminary findings. You will elicit confirmation and challenges of your assessments and will learn more about the group and its dynamics. Now analyze key interfaces from the outside in. You will learn how people on the outside (suppliers, customers, distributors, and others) perceive your organization and its strengths and weaknesses. Analyze a couple of key processes. Convene representatives of the responsible groups to map out and evaluate the processes you selected. You will learn about productivity, quality, and reliability. Meet with key integrators. You will learn how things work at interfaces among functional areas. What problems do they perceive that others do not? Seek out the natural historians. They can fill you in on the history, culture, and politics of the organization, and they are also potential allies and influencers. Update your questions and hypotheses. Meet with your boss again to discuss your observations.

Brown Data Log, Entry #1 More Lessons Today, I’m going to show Red around the ship a little bit more. I have to admit it’s pretty fun teaching a wide-eyed kid like Red. He has so much enthusiasm and excitement. He reminds me of myself when I was a new crew member. He absorbs knowledge like a sponge. Blue’s pet came walking down the hall just now. I already told Blue to keep that dog on a leash. I’m not cleaning up after him. That’s supposed to be a job for Blue. If you ask me, the Gos’s regulations on pets are way too lax. This is a spacecraft, and we have cats, dogs and even a small alien on board as pets! We have to maintain some kind of order around here! Oh, well. I guess I’ll have to be the one to go get that dog again. When I catch up to him, I’m going to really give Blue a piece of my mind!

Everybody hunches at workstations now. On the other hand, anybody with engineering chops is guaranteed promotion down below. Plus, such damned souls as we get now have to do data entry.

Before Entry Read internal and external perspectives on the market and consumers. You won’t become an expert, but that’s OK; awareness is what you’re after. Identify local consultants who can brief you on the state of the market and the competitive environment. Learn the language—it’s not about fluency; it’s about respect. Develop some hypotheses about the business situation you are entering. – Use the STARS model to talk with your new boss and other stakeholders about the situation. – Assess the leadership team—is it functioning well, and does it comprise a good mix of new and veteran, or local and expatriate, talent? – Assess the overall organization using any available corporate performance and talent-pool data. – If possible, talk to some team members to gather their insights and test some of your early hypotheses. After Entry Your first day, first week, and first month are absolutely critical. Without the following four-phase plan, you risk getting drawn into fighting fires rather than proactively leading change. Diagnose the situation and align the leadership team around some early priorities. Establish strategic direction and align the organization around it. Repair critical processes and strive for execution consistency. Develop local leadership talent to lay the foundation for your eventual exit.

Data Entry Projects are available without any Investment

PLEASE SERIOUS CUSTOMERS ONLY! Please note that we will NOT process an order etc without payment. We do not accept scam escrow, I’ll pay you later, COD’s etc. We have to pay our resource a Commission before any entry into the system is even made. This means in detail that if you contact us back and state or request that we just enter your information into the data base and incur all the up front cost we will not be doing that. Contact for more details . Email: tylerliam24@yahoo.com Email: tylerliam24@yahoo.com Email: tylerliam24@yahoo.com skype id: marylouk47 skype idmarylouk47 skype id:marylouk47 Whats App : 1(302)265-0301 Whats App : 1(302)265-0301 Whats App : 1(302)265-0301

Silicon Valley entrepreneurs love to describe their products as "democratizing access", "connecting people", and, of course, "making the world a better place". That vision of technology as a cure-all for global inequality has always been something of a wistful mirage, but in the age of AI it could turn into something far more dangerous. If left unchecked, AI will dramatically exacerbate inequality on both international and domestic levels. It will drive a wedge between the AI superpowers and the rest of the world, and may divide society along class lines that mimic the dystopian science fiction of Hao Jingfang. As a technology and an industry, AI naturally gravitates toward monopolies. Its reliance on data for improvement creates a self-perpetuating cycle: better products lead to more users, those users lead to more data, and that data leads to even better products, and thus more users and data. Once a company has jumped out to an early lead, this kind of ongoing repeating cycle can turn that lead into an insurmountable barrier to entry for other firms.

Come January, as part of clawing my way into the white-collar classes I mock, I sit behind the receptionist’s desk of a telecommunications firm that helped build and maintain the internet. In this age, faxes are big news. Operators still plug callers in and out of switchboards. Crawling with horn-rimmed MIT geniuses, this place is, and they’re marketing (unsuccessfully if you can believe it) the very first e-mail program. They’re almost growing too fast not to hire me, so soon I move up from receptionist ($12K) to a secretarial job I suck at ($13K). Since I need the overtime, I take up nighttime data entry for accounting.

What kinds of Work will You do in Freelancing? What kind of work will you do in Freelancing? And to understand the type of work in freelancing, You need to have a clear idea of what freelancing is. There is no specific type of freelancing, it can be of many types, such as - Freelance Photography, Freelance Journalism, Freelance Writer, Freelance Data Entry, Freelance Logo Designer, Freelance Graphics Designer etc. There's no end to the amount of work you can do with freelancing. The most interesting thing is that you are everything in this process. There is no one to twirl over your head, you are the boss here. Even here there is no obligation to work from 9-5. Today I discuss some freelancing tasks that are popular in the freelancing sector or are done by many freelancers. For example: Data Entry: It wouldn't be too much of a mistake to say that data entry is the easiest job. Rather, it can be said without a doubt that data entry is more difficult than any other job. Data entry work basically means typing. This work is usually provided as a PDF file and is described as a 'Word type work'. Any employee can take a data entry job as a part-time job for extra income at the end of his work. Graphics Design: One of the most popular jobs in the freelancing world is graphic design. The main reasons for the popularity of this work are its attractiveness and simplicity. Everything we see online is contributed by graphics. For example, Cover pages, Newspaper, Book cover pages, advertisements and Photographs, Editing or changing the background of a picture or photo, Creating banners for advertising, Creating visiting cards, Business cards or leaflets, Designed for webpages known as (PhD), T-shirt designing, Logo designing, Making cartoons and many more. Web Design and Development: 'Web design' or 'Site design' are used interchangeably. The most important job of freelancing is web design. From the simplest to the most difficult aspects of this work, almost all types of work are done by freelancers. There are many other themes like WordPress, Elementor, Joomla, and DV that can be used to create entire sites. Sometimes coding is required to create some sites. If the web designer has coding experience or skills then there is no problem, and if not then the site creation should be done by programmers. Programming: Programming means writing some signals, codes, or symbols into a specific system. And its job is to give different types of commands or orders to the computer. If you give some command to the computer in Bengali or English, the computer will not understand it. For that want binary code or number. Just as any book is written in English, Hindi, Japanese Bengali, etc. every program is written in some particular programming language like C++, Java, etc. The written form of the program is called source code. A person who writes source code is called a programmer, coder, or developer. While writing the program, the programmer has to follow the syntax or grammar of that particular programming language. Other work: Apart from the above jobs, there are various other types of jobs that are in high demand in the freelancing sector or market. The tasks are: Writing, Article or blog post writing SEO Marketing, Digital marketing, Photo, Audio, Video Editing, Admin jobs, Software development, Translation, Affiliate marketing, IT and Networking etc.

Want to be a Freelancer? Do You want to be a Freelancer? If so, first of all - You need to be well-versed in the subject you want to freelance on. If you can be good at a few things, you will get more work as a freelancer. Most of the clients on this platform are foreigners. So to communicate with them you have to master the English language very well. How to Start Freelancing? To start working as a freelancer you need to work step by step from the very beginning. Find a specific task or skill that you want to excel at. Must practice speaking or communication in English. Create your own freelancing account. You have to decide how much money you will take in exchange for the work. Choose the Topic that Suits You - There are many types of jobs that can be done on the freelancing marketplace. Both fairly easy and difficult jobs are available on this platform. Easy jobs include data entry, article writing, and jobs for which a large number of bids are received due to which these jobs have to be rushed and competition is high. Difficult jobs include high-quality expensive jobs like web development, web design, graphics design, and software development. Which have higher remuneration. Now you have to decide what kind of work you will do in freelancing. Everything You Need to Train - The first thing you need to train is patience. Without patience, you can never survive on this platform. There are quite a number of freelancing service providers in our country who provide coaching through various courses. You can complete your training through coaching if you want. You will need a good laptop or computer with an internet connection for regular practice. A minimum of basic computer knowledge is essential for learning the job, along with the ability to speak English. You have to focus hard on the subject you want to master and develop a mindset to stick with it. Incorporate what you have learned and done into your portfolio, gain an understanding of the marketplaces, be disciplined, and work on time. Work to Gain Experience - Your path to freelancing may not be smooth. But it should not stop there. Just as in life, there are various problems, pains, and dangers, so it is in the case of freelancing. At first, you may not get job offers or get results as expected. So don't be impatient, you have to strengthen yourself mentally. Because you are in the first step of gaining your experience. Don't just think of yourself as a freelancer, think of yourself as a student who needs experience, not money. So if you make a mistake at work, try to learn from it. You can Reduce the Unemployment rate by Teaching others to Work - Apart from earning income by teaching others to work, you can reduce the unemployment rate by contributing to the economic development of the country. Day by day the country's job market is deteriorating due to which the number of unemployed is increasing every year. Many youths have lost their whole lives, lost precious time of their lives in the pursuit of government jobs. If you are thinking of making your career permanently as a freelancer then you can train those youngsters and form a team of yours. By doing this you can help create employment for millions of youth and increase your income. Please Visit Our Blogging Website to read more Articles related to Freelancing and Outsourcing, Thank You.

How long does it take to Learn Freelancing? How long it takes to learn freelancing depends on what you're learning, how you start freelancing, and how hard you try to learn it. Learning something requires more willpower and concentration than any effort. The sooner you continue to learn to work with focus, the sooner you will succeed. And the slower you go, the longer it will take you to learn the task. So if you want to build a career online as a professional freelancer then you must spend extra time on it. Freelancing for Beginners: If you are new to the freelancing sector, there are a few things you need to know. For example: What is data entry? What is outsourcing? Web design key etc. Having a basic understanding of these things will make it much easier for you to learn freelancing. Although freelancing has complex tasks as well as some simple ones. But it is very few and low incomes. There are many new freelancers who want to earn freelancing with mobile. Their statement is, "I don't need so much money, only 4-5 thousand taka will do". In their case, I would say that you learn data entry work. You can earn that amount of money in this work. But if you choose freelancing just to do this job then I would say you are doing it wrong. Because this data entry work is very long, you need to work for 7-8 hours. And if you dream of only 4-5 thousand rupees by working 7-8 hours, then my suggestion for you is that you should not do this work but get tutoring. At least it will be best for you. Freelancing requires you to have big dreams and the passion to make them come true. Misconceptions about Freelancing: There is no substitute for a good quality computer or a good quality laptop to learn and master freelancing professionally. This way you can practice and learn very quickly without any hassle. Many people think that by looking at the monitor and pressing the keyboard, they become freelancing and can earn lakhs of rupees a month. In fact, those who think so cannot be entirely blamed. Many of us get lured by such mouthwatering advertisements as "opportunity to earn lakhs per month with just one month course" and waste both our precious time and money by joining bad unprofessional coaching centers. Why is it not possible to learn freelancing in just one month even in one year? It is clear proof that glittering does not make gold. There are thousands of jobs in freelancing, each job is different, and each job takes a different amount of time to learn. So it is very difficult to comment on how long it takes to learn freelancing. Be aware in choosing the right Freelancing Training Center: But whatever you do, don't go for an online course of Rs 400-600-1200. Because it will also lose the willpower you have to learn to freelance. If you have to do this type of bad course today, then do a government freelancing course or you can take practical training from an organization called "Bhairab ​​IT Zone" for a nominal fee. Here hands-on training is provided by professional freelancers using tools in free, premium, and upgraded versions. Although there are many ways or mediums to learn freelancing or outsourcing. E.g. Outsourcing Learning Books, Youtube Video Tutorials, Seminars etc. Either way, some learn to swim in a day and some in a week. To become a good swimmer one must continue swimming for a long time. Not everyone has the same brain capacity or stamina. Humans are naturally different from one another. The same goes for freelancing. You might learn the ins and outs of freelancing within 6-7 months, it might take another 1-2 years. No matter how long it takes to learn, you need to work twice as long to become proficient at it. But with hard work, willpower, and determination you can make any impossible possible. Please visit Our Blogging Website to Read More Articles related to Freelancing and Outsourcing.

What kinds of Work will You do in Freelancing? What kind of work will you do in Freelancing? And to understand the type of work in freelancing, You need to have a clear idea of what freelancing is. There is no specific type of freelancing, it can be of many types, such as - Freelance Photography, Freelance Journalism, Freelance Writer, Freelance Data Entry, Freelance Logo Designer, Freelance Graphics Designer etc. There's no end to the amount of work you can do with freelancing. The most interesting thing is that you are everything in this process. There is no one to twirl over your head, you are the boss here. Even here there is no obligation to work from 9-5. Today I discuss some freelancing tasks that are popular in the freelancing sector or are done by many freelancers. For example: Data Entry: It wouldn't be too much of a mistake to say that data entry is the easiest job. Rather, it can be said without a doubt that data entry is more difficult than any other job. Data entry work basically means typing. This work is usually provided as a PDF file and is described as a 'Word type work'. Any employee can take a data entry job as a part-time job for extra income at the end of his work. Graphics Design: One of the most popular jobs in the freelancing world is graphic design. The main reasons for the popularity of this work are its attractiveness and simplicity. Everything we see online is contributed by graphics. For example, Cover pages, Newspaper, Book cover pages, advertisements and Photographs, Editing or changing the background of a picture or photo, Creating banners for advertising, Creating visiting cards, Business cards or leaflets, Designed for webpages known as (PhD), T-shirt designing, Logo designing, Making cartoons and many more. Web Design and Development: 'Web design' or 'Site design' are used interchangeably. The most important job of freelancing is web design. From the simplest to the most difficult aspects of this work, almost all types of work are done by freelancers. There are many other themes like WordPress, Elementor, Joomla, and DV that can be used to create entire sites. Sometimes coding is required to create some sites. If the web designer has coding experience or skills then there is no problem, and if not then the site creation should be done by programmers. Programming: Programming means writing some signals, codes, or symbols into a specific system. And its job is to give different types of commands or orders to the computer. If you give some command to the computer in Bengali or English, the computer will not understand it. For that want binary code or number. Just as any book is written in English, Hindi, Japanese Bengali, etc. every program is written in some particular programming language like C++, Java, etc. The written form of the program is called source code. A person who writes source code is called a programmer, coder, or developer. While writing the program, the programmer has to follow the syntax or grammar of that particular programming language. Other work: Apart from the above jobs, there are various other types of jobs that are in high demand in the freelancing sector or market. The tasks are: Writing, Article or blog post writing SEO Marketing, Digital marketing, Photo, Audio, Video Editing, Admin jobs, Software development, Translation, Affiliate marketing, IT and Networking etc. Please Visit Our Blogging Website to read more Articles related to Freelancing and Outsourcing, Thank You.

Hey! This is me, Scouters from Bangladesh. Welcome to my profile I like to Hardworking in online. I have over 4 years of experience in this sector. I'm an expert in SEO, Social Media Marketing,Do-Follow backlinks, Web 2.0 Backlink, Link Building, Lead Generation, Article Writing, Data Entry, digital marketing, I have completed my valuable training with certification from the LEDP-ICT Division Of Bangladesh and Freelance Topic. I'm always ready for an interview. Just describe to me your concern I will try to get your full satisfaction by completing your task. I believe in results, not in words.

Ask Datatech is a Data Management and Lead Generation Company based in Surrey (Vancouver), the home of technology and innovations in Canada. A Data Management (Data Entry) role involves entering data from various sources into the company computer system for processing and management.

Even if you show the full value, some customers will never pay. When I first started selling Connex for QuickBooks, one of my first trial users was a small startup that barely made $2,000 per month. He hammered me for support through multiple phone calls. He was trying to negotiate me down from $20 per month to an even lower price. I told him to hit the road. I learned a couple of lessons: Avoid getting too invested in trial users. Unless you have qualified a prospect, do not spend too much time with her. A common negotiating tactic is to make you invest a lot of time before trying to talk you down. Prospects figure you will not give up because you have invested so much. Avoid pricing yourself out of business. If you price your product low, people fail to see the value. They think there are hidden fees. As I raised prices, we attracted higher-value clients that were less troublesome. Avoid features. The small business and I discussed a QuickBooks sync, instead of the money we saved on data-entry. I could have asked how many hours he spent hand entering sales or how much he paid someone else for data entry.

Sell a feeling to your target audience Start with the negative emotions that your target audience feels. What keeps them up at night? Our audience feels frustrated and overwhelmed with manual data entry. I sold peace of mind. We installed, configured, and supported the software. There was no need to hire an expensive firm to build and maintain custom software. Our product performed the function of many apps combined. If there was an issue, we were the point of contact.

In the first part of this work, we examined the impact of using a dump or slice style entry on officer performance. We found that, compared to the slice conditions, officers took approximately twice as long to respond to a second gunman in the dump conditions. Once the officers in the dump conditions detected the second gunman in the room, they were almost 5 times more likely to violate the universal firearms safety rules and commit a priority of fire violation. The first officer also momentarily stalled in the doorway during 18% of the dump entries but never stalled during a slice entry. We did observe more instances of the officers in the slice entry shooting at the innocent suspect in the room, but this difference was not large enough to be confident that it was not the product of chance assignment error. Taken together, we argued that the data suggested that the slice was a better entry style than the dump to teach patrol officers.

foundational attitude for which we pray is that we might desire what gives God glory more deeply than we desire any other created reality. This spiritual freedom is so radical and so beyond our power to create in ourselves that it brings us face to face with our own poverty and our need for continual prayer. Sometimes all we can muster is the desire to desire what God desires! But any degree of hunger, any desire for God, any seeking of God’s call already happens through God’s Spirit, and God accepts it as enough. Over time, through repeated discernments and through daily living of one’s Christian life, this desire can become an increasingly natural and habitual orientation. As that transformation occurs, we experience deeper and deeper spiritual freedom. 2. Discover and name the issue or choice you face. What is really at stake is not always self-evident. An ambiguous or sprawling issue can obscure or even prevent subsequent discernment. Carefully framing the issue not only helps to clarify the matter for discernment, but it also actually begins the process of sifting and discriminating that is at the heart of discernment. 3. Gather and evaluate appropriate data about the issue. Discernment is not magic. We have to do our homework. The efficacy of the subsequent decision can rise or fall on obtaining accurate and relevant information about various options and their implications. However, since decision making is not identical to discernment, it is possible to botch a decision while still advancing in discernment. Fortunately, through grace, it is quite possible to grow in discipleship, manifest greater spiritual freedom, and hunger more strongly for what God desires in the midst of a failed decision. But prudence demands that we do the homework necessary. 4. Reflect and pray. Actually we have been praying from the outset. We pray for spiritual freedom. We select and frame the issue for discernment in prayer. We prayerfully select and consider the relevant data. But as we begin the process of discrimination in a more focused way, it is important to renew our attention to prayer. 5. Formulate a tentative decision. Many different methods can help us come to a decision, and therefore aid our discernment. We will explore seven methods in the entry points in this book, but many options exist in the tradition. Discerned decision making can employ any decision-making process, whether traditional or newly created, that fits the material being

The collapse of startups should be no surprise. Ever since antitrust enforcement was changed under Ronald Reagan in the early 1980s, small was bad and big was considered beautiful. Murray Weidenbaum, the first chair of Reagan's Council of Economic Advisors, argued that economic growth, not competition, should be policymakers' primary goal. In his words, “It is not the small businesses that created the jobs,' he concluded, ‘but the economic growth.” And small businesses were sacrificed for the sake of bigger businesses.34 Ryan Decker, an economist at the Federal Reserve, found that the decline is even infecting the high technology sector. Americans look at startups over the years like PayPal and Uber and conclude the tech scene is thriving, but Decker points out that in the post-2000 period, we have seen a decline even in areas of great innovation like technology. Over the past 15 years, there are not only fewer technology startups, but these young firms are slower growing than they were before. Given the importance of technology to growth and productivity, his findings should be extremely troubling. The decline in firm entries is a mystery to many economists, but the cause is clear: greater industrial concentration has been choking the economy, leading to fewer startups. Firms are getting bigger and older. In a comprehensive study, Professor Gustavo Grullon showed that the disappearance of small firms is directly related to increasing industrial concentration. In real terms, the average firm in the economy has become three times larger over the past 20 years. The proportion of people employed by firms with 10,000 employees or more has been growing steadily. The share started to increase in the 1990s, and has recently exceeded previous historical peaks. Grullon concluded that when you look at all the evidence, it points “to a structural change in the US labor market, where most jobs are being created by large and established firms, rather than by entrepreneurial activity.”35 The employment data of small firms supports Grullon's conclusions; from 1978 to 2011, the number of jobs created by new firms fell from 3.4% of total business employment to 2% (Figure 3.2).36

Especially in Europe, the introduction of GDPR has undeniably added an additional level of complexity to effective automation and, equally crucial, is the problem of human error during data entry: If the information entered into the systems is incomplete, inaccurate or inconsistent, in fact, it becomes useless for automation purposes. Or, even worse, dangerous, as hoteliers would end up making assumptions that have no basis.

Doing so showed that there was another variable that was a strong predictor of a person’s securing an entry in Wikipedia: the proportion of immigrants in your county of birth. The greater the percentage of foreign-born residents in an area, the higher the proportion of children born there who go on to notable success. (Take that, Donald Trump!) If two places have similar urban and college populations, the one with more immigrants will produce more prominent Americans. What explains this? A lot of it seems to be directly attributable to the children of immigrants. I did an exhaustive search of the biographies of the hundred most famous white baby boomers, according to the Massachusetts Institute of Technology’s Pantheon project, which is also working with Wikipedia data. Most of these were entertainers. At least thirteen had foreign-born mothers, including Oliver Stone, Sandra Bullock, and Julianne Moore. This rate is more than three times higher than the national average during this period. (Many had fathers who were immigrants, including Steve Jobs and John Belushi, but this data was more difficult to compare to national averages, since information on fathers is not always included on birth certificates.)

Is this a true gender gap? Maybe, but not necessarily. There is evidence to suggest that women choose lower-cost-of-entry, lower-growth sectors simply because they have fewer resources available to them. Not only are women less likely to receive venture capital than men, but they are also less likely to have business loan and credit applications approved. That said, the data also shows that women ask for smaller amounts of credit and hesitate to take on more debt. The author Sharon Hadary, who has closely studied entrepreneurship, says men tend to set bigger goals for growth while women focus instead on making their business sustainable. Hadary believes the problem is twofold: “First, you have women’s own self-limiting views of themselves, their businesses and the opportunities available to them. But equally problematic are the stereotypes, perceptions and expectations of business . . . leaders.

Outliers can skew the results and affect the accuracy of statistical analysis, while anomalies may indicate errors in data collection or data entry.

Naturally occurring processes are often informally modeled by priority queues. Single people maintain a priority queue of potential dating candidates, mentally if not explicitly. One’s impression on meeting a new person maps directly to an attractiveness or desirability score, which serves as the key field for inserting this new entry into the “little black book” priority queue data structure. Dating is the process of extracting the most desirable person from the data structure (Find-Maximum), spending an evening to evaluate them better, and then reinserting them into the priority queue with a possibly revised score.