Big data has been generating a huge amount of noise over the past few years. It’s overhyped and under… well, not particularly understood by most people. However, the hype is starting to settle, the technology is improving, and businesses are getting more comfortable with data analytics. It’s leading to more accurate predictions, smarter choices, and a whole new industry of self-serve data-as-a-service.

As the hype settles, businesses are starting to become a bit more critical of their data analysts as well. It’s time for the return on the sizeable investments that have been made to start showing. Yes, big data is leaving its infancy and some major changes are coming. To make sure you stay ahead of the curve, let’s examine 5 trends in big data everyone will be paying attention to in 2017.     

The big cloud

One of the reasons for the slow adoption of big data analytics by small to mid-size business has been the cost of building and maintaining a database. As cloud technology becomes more prevalent, it’s opening the doors on data analytics to a much wider range of businesses.

Even large scale and Fortune 500 companies that have maintained their own databases for years are making the switch to the cloud. Frankly, it’s just more convenient. Having all of your data on the cloud makes it readily accessible from anywhere in the world, which reduces the need for traditional office spaces.

Using a cloud provider for big data storage also alleviates some of the security responsibilities that businesses have struggled with in the past. The cloud host deals with most of the security updates and threat prevention while businesses get to focus on what’s important to them, analyzing that data and turning it into dollars.     

Artificial intelligence

If anything has been making a larger buzz in the business world than big data over the past couple years, it would be AI. Our artificial intelligence is becoming truly smart thanks to new deep learning software. Those advances will have a major impact on big data.

Besides database maintenance, proper, focused, unbiased, analyzation of big data has been one of the major pain points for businesses. New advanced AI will solve that issue by simplifying the data analytics process. Instead of writing(or buying) a program to interpret data, people will simply ask their AI unit to analyze the data for them and generate the answer to specific questions.

An AI unit replacing or more likely, working in concert with traditional data analysts will save businesses time and money.

New data sources

As the internet of things continues to take shape, the wealth of new data that will be created is immense. However, the IoT isn’t the only new data source that will be changing the game in 2017. This year, many companies and organizations are expected to begin entering all of their historical data that’s saved in hard format, paper, pictures, film, into their databases to generate a more accurate view of their history.

Blockchain

Blockchain has been right up there with big data and AI in the hype department for the past few years. For those of you who don’t know, blockchain is a type of decentralized database that stores information in blocks (technically bits) that link together as new information is added. It’s what the cryptocurrency Bitcoin runs on.

While blockchain isn’t necessary for every business, banks and healthcare providers have been taking notice of blockchain’s ability to securely store data in a way that is easy to view. Over the next couple years, what started as a small push will develop into a tidal wave of businesses in the health and financial sectors making the switch to blockchain.   

The hype settles

As with all things, what goes up must come down. The hype surrounding big data recently has led to a lot of misinformation, wasted time, and most importantly from a business perspective, wasted revenue. Now that the technology is becoming more commonplace and the hype is starting to diminish, data analytics providers are going to start noticing a change in their client’s attitudes from, “You’re a magician, I have faith,” to “It’s been over a year, time to start showing some results.”

 

It’s safe to say that big data is no longer in its infancy, it’s in its adolescence. There’s still some growing pains happening and plenty of mistakes to be made, but one thing is certain, businesses that don’t start mastering data analytics now will find it nearly impossible to play catch-up with their competitors down the road.