Data on its own is nothing but a string of 0s and 1s, but now in today’s world big data is a reality. Technology goes together well with data: the more we advance in technology, the more data we have to manage. To give you a rough idea about the volume of such data, look no further than Wal-Mart. They collect and manage 2.5 petabytes (10 bytes) of data within an hour of the customer’s transactions. It’s tremendous.
Records show that data is growing at a rate of about 59 percent per year globally. Three V’s characterize this growth:
- Volume: Exponential increase in transactions in today’s world makes the volume an issue. Volume is not only a storage issue, but also a giant analysis issue.
- Velocity: The speed with which data streams are created and made available to access defines the velocity. Velocity thus involves both matching the speed of data production and the speed of data processing to meet demand.
- Variety: Data could be of various varieties, could be structured and also could be unstructured.
What is Big Data Analytics?
Big data analytics is the process, by which data analysts study big hubs of data to reveal hidden patterns, correlations, and other useful information that could be used to make better business decisions. Technologies like NoSQL databases, MapReduce, and Hadoop are usually used for this purpose. The sole purpose of big data analytics is to help big organizations make better business decisions to maximize their profit.
Why Big Data Analytics? “The Game Changer”
Consider that your organization handles and stores traffic of billions of rows of data, which would possibly have millions of data combinations. High performance analytics is required to analyze that amount of data traffic in order to figure out what is important and what is not. And this is something big firms need.
Almost 20 years ago, big data analysis became a game changer for marketing as well as for sales, because the data reflected everything from insights into the customer’s needs and behaviors to the products in demand. The companies which successfully turned this data into actionable results improved their profit. One very interesting fact that came out is that the most successful companies are not those who have the majority of the data, but those who use their data in the most efficient way possible.
The Future: “Drawn by Big Data”
Today, companies are looking for new ways to transform their business, via data, to get insight to make the best possible decisions. So advancing technological trends in big data and analytics has not only revolutionized the big data world, but it took the employee-analysts to a different level as well.
We also have the new analytics 3.0 revolution to consider: it's the most advanced form of analytics to date when compared to analytics 1.0 and analytics 2.0. Analytics 3.0 will bring powerful data gathering and tremendous analysis methods, and not just to the company’s operations. It will also embed data into various products and services customers buy.
So, Perhaps big data will be a way of defining a paradigm shift to data intensive collaboration, where processes reinforce traditional database approaches. Companies are hiring the best data analysts available in the market to maximize their profit. This competition among big firms and gradual increases in skills of analysts will take big data and analytics to a different level.
Image Credit: Wikimedia Commons