Original image by JD Hancock
Big Data: A Brief History
I’ve heard that the term “big data” was used as early as 2005, but some believe that Roger Magolous came up with the term. In a 2009 video interview, he defined big data as, “when you have to think and worry about the size of the data”.
For many, big data is nothing new. Banks, major retailers, telecommunications providers and governments have been collecting and analyzing vast amounts of data for years. For the most part, this has been structured data that has been stored in databases for record keeping, accounting, reporting and compliance purposes.
Data growth and the need for more storage led companies to deploy comprehensive and expensive storage architectures and technologies such as network attached storage and storage area networks. These technologies also drove the need to increase the bandwidth, speed, security and performance of their wide area and local area networks.
Some of these companies have taken a storage-centric approach that focuses on putting enough “iron” in place to store the increasing amounts of data without any thoughts or plans on how to use it. Others have taking an information management approach because they see data as something to use to gain business insights and make better decisions that drive profit.
Big Data Today
Data grows and demand for storage resources increases and the mindset of the IT department is, wisely so, to continue to collect, store and archive any data for future access. This is because the cost of hard disk space is inexpensive, and virtualization is allowing organizations to squeeze as much computational power and storage as possible out of their existing infrastructures.
As I mentioned earlier, some companies analyze their data by taking an information management approach. They do things like segment customers based on risk, revenue and loyalty. Other companies analyze their data to better optimize inventory and predict the popularity of a product. They do this by exporting structured data into spreadsheets or more sophisticated analytics tools. These organizations are better suited to take advantage of big data.
Why Should You Care About Big Data?
Companies are using big data to uncover new sales opportunities, provide better customer service and find more efficient ways to manage inventory and payables. Google is using big data to plot flu trends to estimate flu activity in twenty-eight countries. Amazon.com uses big data to recommend products that you may like based on factors such as your purchase history. An electronics retailer can compare web traffic to point-of-sale data and has found a correlation between online and in-store purchasing habits.
This begs the question: What can you find in your data?
When you start to think about big data, consider both the size of your data and whether you are using it to your organization’s advantage. How does your organization collect, analyze and manipulate data so you can learn more about your customers and your business? Also ask how you are using data to become more profitable, responsive, competitive and flexible.