Yahoo CEO Marissa Mayer said that "big data" will have a biggerimpact than the Internet. Consider how the Internet completelychanged our lives. It's hard to imagine anything, let alone thevague concept of "big data," having that type of impact.

Yet, if you have read any article the past year about a legaltechnology issue, then you have undoubtedly heard about big data.There's still a lot of confusion about big data, its power, itspotential, and what it means for lawyers.

The first step to understanding big data is to define it. Manypeople think big data just means a lot of data. That's onlypartially true. It is generally accepted that big data "refers todata sets whose size is beyond the ability of typical databasesoftware tools to capture, store, manage, and analyze."

Yet, at its core, big data is really about dataanalytics—sophisticated algorithms that are being applied toincomprehensibly large volumes of data. We create a staggeringamount of data each day. For several years, computer scientistshave been developing more and more powerful ways to harness theincredible volume of data for all sorts of purposes, such asmarketing, medical research and business intelligence. This is nota recent phenomenon. The big data revolution is a quiet one. It hasbeen going on for years, right under our noses.

Every time we visit a website or send an email, it is likelythat some computer somewhere is tracking our movements and addingto a database that contains our online profile. Researchers usethese databases, through highly complex mathematical algorithms, tofind patterns in data so they can predict future buying preferencesand decisions based on our on-line activities. This information isthen used to sell highly focused and effective advertising. Thistype of data analytics has been going on for years, but many of ushave been completely oblivious to it.

Big data has become today's next phenomenon because the sciencebehind data analytics has continued to grow and is now being usedto in numerous areas of our lives—more than just advertising. Atthe same time, our ability to analyze data has improved, the amountof data we create is increasing dramatically, and our ability tostore, process and transfer that data has improved tremendously. Wehave so much data about so many different aspects of the world, andwe now have the capacity to store and collect it. This is a dreamfor big data researchers.

They are figuring how to combine and review these immense datasets together. The result is that they are finding patterns inhuman conduct and nature that would have never been found withoutthe ability to analyze these large data sets.

In the past, in order to discover or research something new,researchers would postulate a theory, gather data to test it, usestatistical sampling to extrapolate from that data and then reach aconclusion. But this process has a major limitation: The researchermust pose the questions before the sample data is collected.

Big data is fundamentally changing this process. Rather thancreating a theory and gathering sample data to test it, which mayin itself skew the results, researchers are gathering a massiveamount of data and then looking for patterns and correlations. Indoing so, they are letting the data speak for itself. By looking atmassive amounts of data objectively (rather than sample data),researchers are now making discoveries that are not limited byhuman instinct and intuition. This does not mean big data replaceshuman instinct or intuition. But sometimes, human instinct andintuition are skewed by the natural desire to figure out whysomething happened; for example, why a disease starts. Instead oflooking for why, however, big data focuses on what—that is, what'slikely to happen next.

In their excellent book, "Big Data: A Revolution That WillTransform How We Live and Work," authors Kenneth Cukier and ViktorMayer-Schoenberger discuss this dichotomy and give a great exampleof how big data is being used to predict the what in medicineinstead of the why. Researchers in Canada used big data to spotinfections in premature babies before any overt symptoms appeared.They took 16 vital signs, like heartbeat, body temperature,respiration, and blood-oxygen levels, and turned that into a streamof information with more than 1,000 data points per second. Usingthis data set, they were able to find correlations and connectionsin the data that helped predict the existence of an infectionbefore it surfaced. Big data doesn't explain why the infectionstarts, but it can help predict what is likely to happen next whencertain factors are present at the same time.

In this sense, big data is giving researchers a view of theworld never seen before. We are moving from a world where data wasused to explain or support a discovery to a world where data — itsconnections and correlations — is the discovery. In this sense, bigdata is a collision between math and sociology that promises tochange the way we see and analyze our world.

Today, businesses of all kinds are using big data to improvecustomer service, analyze their competition, manage supply-chains,monitor customer markets, follow societal trends, maintain employeerelations, target advertising, find emerging markets, and expediteproduct innovation. Because technology developments are making iteasier to derive value from analyzing data, sophisticatedbusinesses are focusing more than ever on data analytics. Theseanalytics are being used to generate revenue. This monetization ofdata is fueling the big data explosion. And, as we will explorelater, this is the main the reason why lawyers need to understandbig data.