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This microbook is a summary/original review based on the book: Big Data: Does Size Matter?
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You've probably heard the term "Big Data" out there. But do you know what that means and what are its implications for the new digital age and the future? In 'Big Data: Does Size Matter?', Timandra Harkness explores concepts and possibilities of using Big Data. Also, it discusses the limits and possible issues that are brought about by the new avalanche of data, such as privacy issues.
In today's world, companies need to take advantage of technological advances to create competitive benefits and the use of Big Data has become essential. Also, as a consumer, you also need to understand the implications of Big Data in your personal life. Come with 12min and learn more about Big Data and how to use it to your advantage in this microbook!
The term "Big Data" was first used in 2005. It refers to any large volume of data that needs to be stored and analyzed by a computer.
Generally speaking, we are talking about data sets so large that a human being would not be able to analyze. However, the best way to define Big Data is to forget the volume and consider the following issues:
Dimensions or diversity: Big Data data is collected at all times and on a large scale. A good example would be the following: to analyze how much a single dog eats observing it for a few days, is not Big Data. However, picking up a large number of puppies and examining their eating habits by combining the data with other factors such as time, location, dog's age, health problems, and breed would give us a complete picture of how much food a dog eats when and why.
Automation: Big Data is not data collected by a person going door to door with a clipboard. Data is usually collected automatically, without being noticed, when we swipe our credit card, when we go through a ticket gate, when we Google something, or buy a bus ticket. Almost without exception, every time we come into contact with a machine, data is being collected.
Time: The Big Data world is taking advantage of extended periods of time and stored data, and this is how data is used to understand patterns and make predictions. Big Data data is not static, there is continuous feedback, and it is always changing and flowing.
Artificial Intelligence: Analyzing Big Data data relies on computers to make predictions based on numbers. Humans only get the data after they go through the machines, which filter what is most important.
Big Data, in practice, means relying on computers to collect and analyze large volumes of data automatically. Data is gathered from many places and combined with a variety of factors, taking into account extended periods of time of time to understand patterns and make predictions.
The Big Data era has brought unimaginable levels of intelligence to understand consumer behavior. The data can tell us what people are buying and when they are buying it, and in some cases even what they are thinking of buying. Companies do this in a variety of ways, all of them involving Big Data.
Before the 1990s, supermarket customers were encouraged through coupon deals, which companies used to analyze and understand consumer behavior. Over time, store loyalty cards replaced coupons which not only offered rewards but also could record information about people's shopping habits to build a customer profile. If for example, you are buying diapers, it is easy for the store to understand that you will soon buy school supplies, and then create a customized marketing campaign for your preferences. Stores no longer need to waste money targeting 90% of the people who were not interested in organic food and could instead focus only on the exact 10% who were.
Targeted Marketing is not the only way to use Big Data. Today, companies are building profiles of their model clients according to their virtual digital traces. For example, a British loan company can offer short-term loans with high-interest rates to those who need fast cash. They can maintain an impressive 7% default rate. How do they do that? Through Facebook! After getting people's potential borrowers’ email addresses, the company's computers look for their profiles on social networks, observe who their friends are and analyze the financial profile of each potential customer, to decide if they will offer credit or not.
Social networking profiles are also used to show custom ads. This customization occurs, for example, when you look at the profile of a restaurant on Instagram, and an ad appears the next day, reminding you of that restaurant and offering you a discount coupon. Everything you do on social networks is being saved, analyzed, and used to target personalized ads.
Companies have adopted Big Data using loyalty cards programs and their credit card history to understand their buying habits and build a profile of their spending habits. Some companies go even further by monitoring their social networks for information and then using artificial intelligence to make "assumptions" about what you might be interested in buying in the future. In a way, thanks to Big Data, some companies know you better than you know yourself.
Big Data is being used to make our communities safer, whether it's recording internal TV circuitry from public spaces for anomalies or building maps to help police catch criminals before they commit crimes. But is there any problem with that? Can the use of Big Data do more harm than good?
In London, police publish maps which show where crimes have happened in a given zip code. This information not only helps citizens plan when they will go somewhere but also helps potential visitors and real estate buyers to know more about a particular area. In Los Angeles, police use a data-analysis tool called PredPol, which also uses crime data to show where crimes are most likely to happen at any time. This predictability means that the police can organize to get to a neighborhood before a crime happens.
We can use Big Data to help us avoid areas where crimes are most likely to happen, and we can improve security since police can predict when crimes will occur.
With so much information available about voters' profile, political parties would not be smart if they decided to ignore the opportunities that this information has to offer. However, there is a thin line between what is morally acceptable and what is not, and the public must question their motivations and means.
In the 2008 US elections, Democrats used software called NationBuilder, which allowed the party to monitor what people were saying on social networks from their emails. A person can express their political preferences by volunteering at a school or complaining about their neighborhood problems on Twitter. Using this type of information, a candidate can direct communication regarding the policies that are most important to each voter. That's what conservatives did in a recent election: they identified undecided voters on social networks, built a profile of their motivations and concerns, and sent personalized letters on these issues. This target mailing helped them win the election.
However, while we are open to the analysis of politicians, on the other hand, we can also analyze and monitor them more easily. The Big Data world has made it possible to trace everything politicians say, how they vote, and how often they participate in debates. In the past, it would be impossible to know all this about our elected representatives, unless we went after the written records. Today, we can find all this information in seconds.
It's a two-way street. Politicians are using the data to get closer to voters as well as to inform their proposals and we citizens are better able to monitor them than ever before. However, we need to remember that data can be manipulated and that computational data cannot replace voter analysis. Knowing your local representatives is a much better way to understand his/her goals.
We often hear that if we have nothing to hide, then we should not be afraid to make our data public. But is this the case? Is a transparent and open society better for everyone or should we take action to protect our private lives?
Think about it: the mapping company CartoDB has created a map with all the trips made by the taxis in New York, every day and every hour. The information is used to monitor travel time and congestion. It may sound exciting, but imagine if you were a public person and the press knew where you live. They could analyze all taxi journeys leaving your address, and potentially monitor your entire life.
Another potentially apocalyptic scenario: Imagine if your medical data were made public and made available to everyone. Would we always be honest with our doctors? If we thought our bosses could have access to our medical records, would we be less likely to consult with them? Anxiety about privacy could lead to medical emergencies and even death, for in a world without privacy we may be reluctant to approach doctors on sensitive issues.
Even if we think we have nothing to hide, we need to be aware of how and with whom we are sharing our data. We need to ask ourselves all the time if we're comfortable getting our phone calls tracked, our private photos accessed, or our internet searches saved by a company liable to be hacked.
It is possible to take action to keep some of our privacy and enjoy anonymity. Even if you have nothing to hide, it is important to protect your privacy to avoid an avalanche of sales leads because some company has sold your data or posted it on the internet. You may also want to browse the internet without being targeted by custom advertisements.
To preserve your private life, you should question every time someone asks for your contact details. Will you get something in return or can you live without it? If you do not need to share your data, do not do it. On social networks, it may be a good idea to decrease the frequency and content of the information you share. If you tag a friend on a walk in the park when he should be at work, you may be risking his job. Protecting your passwords is important as well. Not using the same password for everything is essential. If you usually forget a lot of different passwords, you can use a password management tool. Consider the security questions as well. How hard is it for someone to find out your father’s middle name? Regarding your mobile, you need to be selective about which apps you are downloading and carefully check what they request to access your information.
Privacy is your right, and it 's hard to live an authentic life when someone is watching us. In Big Data era, we need to be aware of when we are sharing our data and think very carefully about whether or not we want to share it.
The term "Big Data" is used to describe large amounts of data which are gathered automatically from numerous sources, cross-referencing and generating patterns, which can make predictions. Businesses use Big Data to build customer profiles and receive permission to collect data in exchange for discounts or rewards. Companies also use Big Data in less transparent ways, even accessing and analyzing our activities on social networks.
The possibilities for the Big Data world are endless and are sure to bring many benefits in the future. However, we can not forget that computers can not make moral judgments. Also, since privacy is a grave matter, we must take responsibility for protecting our data. We know that Big Data is something that has come to stay and that is changing the way we live, so we need to make sure we are in control and know what we are sharing.
12min tip: How about discovering five things that Big Data does for your health?
Timandra Harkness is a writer, comedian, and broadcaster and has been presenting in scientific, mathematical and statistical subjects since the last days of the 20th century. She has written about trips to the Sunday Times, motoring for the Telegraph, science and technology for WIRED, BBC Focus Magazine and Men's Health Magazine, and is a regular voice on BBC... (Read more)
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