Marketing was one of the first industries to leverage big data in a strategic and lucrative way. Marketing has wrangled data for tremendous potential in the areas of lead generation, social marketing, content marketing, email personalization, and more. But even within the industry that could very well be hailed as a pioneer of big data, relatively little is understood about it. What is big data? Where did it come from? Where is it going? Let's take a peek.
1. Nobody Can Agree on What Big Data Is
The number of definitions you receive when asking, "What is big data?" is directly related to how many people you ask. Ask 5, you get 5 answers. Ask 25, you'll get 25. What is generally accepted and agreed upon is that big data is defined according to the "3 V's" (or 4 or 5, again, depending on whom you ask). Those are: Volume, Variety, Velocity (and potentially, Veracity and Value).
2. Big Data is More About Variety Than Volume
Whether or not you agree that it takes 3 V's, 4 V's, or 5 V's, it's also generally agreed that Variety is probably the most distinguishing aspect of big data. Lots and lots of data really doesn't have any more value than a smaller set of data. That's especially true if the smaller sets consist of cleaner data. What sets big data apart is its variety. Let us explain.
If you only have data on how much your customers spend with your company in a single purchase, that doesn't tell you much. But combine that data with data on which ones ordered add-on products, which took advantage of coupons or special offers, which are return customers, and whether they pay using credit or debit card -- now you've got good info. That's why Variety is the most potent aspect of big data.
3. The Concept is Anything but New
The first major undertaking involving data (unless you count the advent of accounting practices 7,000 years ago, which we don't) was the Social Security system, which was started in 1937. The federal government was charged with tracking contributions to the program from 26 million American citizens and over 3 million employers. This was before the era of modern computing. IBM had to create a special punch card reading machine to get it done. Data processing machines didn't hit the scene until 1943, and the mainframe computer (not capable of doing anything like handle today's big data) didn't hit the market until 1966. Though that was the conception of big data, that term wasn't used until 2005 by Roger Mougalas from O'Reilly Media.
4. Machine Learning & Artificial Intelligence are Impossible Without Big Data
You've likely heard the lofty (crazy?) predictions (threats?) by tech geniuses like Bill Gates and Stephen Hawking that the world will one day be taken over by computers. That won't actually happen as long as humans have power switches, but there have been huge strides made in the field of machine learning, also known as artificial intelligence. This is the force behind robotics that can make assessments based on information they have obtained (learned) previously. All of this hocus pocus is really just big data running on data streaming tools conducting real-time analytics. It isn't anything like human thought, but it is quite impressive!
5. Big Data Privacy Issues Were Around Long Before Massive Amounts of Data
The privacy issues that keep the marketers, government legislators, and the general public up late at night aren't new, either. In fact, the first questions about personal privacy relative to the massive amounts of data collected on people were brought up way back in 1971 by Arthur Miller in his book The Assault on Privacy.
6. Big Data is Testing the Limits of Modern Data Storage Capabilities
Though memory, storage capabilities, processing power, and the entirety of the tech industry has come light-years since 1943, big data is actually stressing the capabilities of storage capacity today. For a comparison, the smartphone in your pocket holds more computing power than all of the banks of computers it took to put man on the moon. Big data isn't measured in gigabytes or terabytes. It is measured in exabytes. One exabyte is the equivalent of all the data in 1,600,000,000,000 books. That is big data.
ReachForce helps marketers increase revenue contribution by solving some of their toughest data management problems. We understand the challenges of results-driven marketers and provide solutions to make initiatives like marketing automation, personalization and predictive marketing better. Whether you have an acute pain to solve today or prefer to grow your capabilities over time, ReachForce can unify, clean and enrich prospect and customer lifecycle data in your business, and do it at your own pace.