Big Data has been trumpeted as a vital resource that can help companies better understand customer behavior, make better business decisions, and develop new products and services tailored to the needs of their target markets. Big Data is what enabled Nate Silver to make astoundingly accurate predictions during the 2012 presidential election—he correctly predicted the winner of the electoral votes in all 50 states. It’s also what drove Billy Beane’s “Moneyball” approach to scouting baseball players.
What Does “Big Data” Actually Mean?
Big Data is typically described using the “3Vs”: volume, velocity, and variety. Volume is pretty self-explanatory—there is a lot of data out there. Velocity refers to the speed with which data is created, and the speed at which it must be processed. Thanks in part to social media, new data is constantly being created and shared in real time, so meaningful processing requires a tight feedback loop. Variety refers to the multiple formats in which data can created and stored—everything from a CSV file to a video or a text message.
Gartner defines Big Data this way: “Big Data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery, and process optimization.”
According to A.T. Kearney, global spending on Big Data is growing by nearly 30 percent each year and is likely to reach $114 billion by 2018.
Get a Handle on Your “Small Data” First
Clearly, Big Data is sexy right now. But most companies could be better served by focusing on small data, not Big Data. Rather than a vast, unwieldy collection of a wide variety of data, small data refers to a limited information set, such as how much a shopper spends during each visit to your store.
Think of Maslow’s hierarchy of needs. Humans must meet their basic needs, like access to food, water, and shelter, before higher needs, like love and self-esteem, can be addressed. Similarly, companies must have a good grasp of small data—accurate information about sales force performance and cash flow, for instance—before delving into Big Data.
If you can’t easily visualize the most basic information about your company, like how quickly your customer service representatives are answering the phone, then you should spend some time and energy assessing that data first. In other words, make sure you have a strong understanding of all relevant limited information sets before you branch out into larger data sets.
Blend Data Points Together for Better Data and Focus on Use Cases
For a true 360-degree view of your business, you need a blend of data based on specific use cases. For example, you should be able to track leads through the sales pipeline and correlate social media interactions with buying behavior. Amazon’s recommendation engine is a great example of how blended data can be used to increase sales. Amazon’s “Recommended for You” suggestions are based on your own purchasing habits, as well as the purchase data from millions of other shoppers. Amazon analyzes buying behaviors and looks for patterns in order to make useful recommendations that will actually increase the likelihood of you making another purchase.
The bottom line is that Big Data isn’t always the answer–there is no one-size-fits-all solution. In order to develop effective business insights, you first have to understand the problem you’re trying to solve. Then, you have to identify the underlying data that can help you solve it. Finally, you must be able to present the data in an easily understandable format.
Now, easier-to-use apps and tools like visualization are democratizing the real value of Big Data. With visual analytics tools from iCharts, you can integrate data from multiple systems and quickly create interactive reports and intuitive charts and graphs from real-time data. We’re a Google Cloud partner and our solutions integrate seamlessly with Google BigQuery, so you can easily analyze your data, without expensive customizations.
Gain access to better data with business analytics and reporting solutions from iCharts.
3 Vs image source: Foresight Investor