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Big Data Feels the Need, The Need for Speed

Just like other recent tech innovations — mobile, cloud, social, etc. — big data has proven its worth. Organizations no longer question its role in business; it’s now just a matter of deciding which tools to use and determining which tasks to hand over to analytics. The future of big data is secure: but what does that look like? Much like Maverick and Goose, big data feels the need for speed. The future of data analytics is blindingly fast. Don’t look now, but the future is about to catch up with us.

What’s Driving the Need for Real-Time Analytics?

Big data

Users are used to high-speed Internet access at work, home, and on the go. Waiting even a few moments for an answer isn’t acceptable. This means that the machines have to do the super fast analytics, because humans are just too slow.

Before discussing what tools can deliver BI at the speed of light, it pays to take a look at the forces driving the need for super fast analytics. Sure, people will still take their time analyzing stuff like how to build better transportation systems and what commodities people buy the most of during an economic recession. But the analytics that will mold and shape the future have to happen in real time, and humans just don’t have a place in that kind of speedy analytics.

Today’s users, spoiled by high-speed Internet access and the speed and convenience of 4G mobile connectivity, are no longer willing to wait for anything. When they start shopping for their vacation plans, they expect the perfect deal to appear magically within seconds of launching their search. Similarly, they demand that their credit cards be approved instantaneously when they try to score that tablet on Amazon, and they expect that the purchase will come with recommendations for the right accessories, like a car charger and a shock-proof case.

What Tools are Being Used to Provide Real-Time Analytics?

Big data

Relational databases are out for real-time analytics. That job calls for a speedier DB like NoSQL and some zippy analytical tools like Hadoop and Spark.

Delivering a highly relevant travel package in real time means that there’s no time for a person to sit down, review the traveler’s preferences and search history, and develop a vacation package that they’re likely to be interested in. This kind of shopping experience demands a database that can respond far faster than the typical relational database (SQL), and apps that can draw the data, conduct real-time analytics, and deliver a response back to the DB for the customer — all before the customer decides to pop over to a competitor’s site instead.

The DB of the future is a NoSQL database that can capture data on the fly, deliver it to Hadoop or Spark for analysis, and get a response at the ready for the customer in real time. Cassandra, Aerospike, and MangoDB are the most popular choices for NoSQL DBs. MapReduce is slowly falling out of vogue for analytics, as Spark proves much faster and has come a long way in terms of reliability.

This one-two punch of speedy DB plus analytics can do more than deliver our vacationer with the right deal on her Maui trip; it is also critical for real-time analysis of her credit card transactions, so that if her card goes missing at LAX airport, the fraudulent charges can be identified and stopped before the thieves run up a hefty tab.

Speedy analytics is also what it’s going to take to identify and thwart network intruders in order to stop the onslaught of data breaches, and it’s also what drives recommendation engines, which are hallmarks of e-commerce success stories like Amazon.

Are you ready to start building a DB capable of real-time analytics to keep up with your competitors in the age of big data at light-speed? Bigstep can help. Find out why people are turning to the speed and capabilities of the Full Metal Cloud by reading our customer success stories.

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