Planning for Big Data Analytics in 2017

Big Data Analytics in 2017

Organizations are making moves toward using big data to make better decisions and cater to customer needs more effectively, which leads to the generation of more revenue. Earlier this year, the Economist Intelligence Unit reported that in a survey of professionals from across multiple industries, 60 percent of them cited data as a key revenue generator for their organizations.

What's more, 83 percent of them said that thanks to big data, existing services and products were becoming more profitable. Given these numbers, it's critical for enterprises around the globe to improve their relationships with big data and take steps to incorporate it into their operations.

"Deep learning shows potential for helping to solve business problems by using algorithms to detect patterns."

Big Data on the Rise: Some Trends to Watch Out For

A Gartner survey from the beginning of 2015 predicted that by 2017, 75 percent of organizations would be investing or planning to invest in big data. Although the IT research firm has since released numbers that indicate these kinds of investments are slowing down as we enter 2017, according to 451 Research, the total data market is expected to grow from $69.6 billion in 2015 to $132.3 billion in 2020.

All of this is to say that companies are still excited about the potential advantages that big data analytics bring to the table. There are a few key trends that will emerge as we move into 2017, including:

connected electronics inside the letters: IOT
The Internet of Things shows a lot of promise, and with that promise comes a mountain of data waiting to be analyzed.

  • The Internet of Things: The amount of data created by the IoT is astounding; by 2020, there will be 20.8 billion connected objects in use, and they each generate data. In 2017, it's going to become even more important for organizations to learn how to incorporate the insights delivered by the IoT into their operations.
  • Deep Learning: This term refers to the set of machine-learning techniques based on neural networking. Information Management contributor Bharadwaj Chivukula noted that although this technology is still evolving, it shows potential for helping to solve business problems by using algorithms to detect patterns in structured and unstructured data.
  • Cloud Computing: The cloud is being utilized by as many as 95 percent of enterprises, according to RightScale, and it's a critical part of the IT infrastructure of many organizations. As more uses are found for these kinds of virtual environments, companies within every market are going to need to figure out how to harness the cloud's power. The secret to this lies in figuring out how to gather, store and unlock the data on various APIs.

Using the Right Tools

In order to plan for big data analytics in 2017, it's critical to consider the trends and popular uses for the technology in terms of how enterprises, small businesses and everyone in between is using it. The above trends are only a few of the current avenues on the horizon as we move into 2017. Organizations are going to need the right data storage technologies and analytics tools in order to get the most out of the information generated by the IoT and the cloud.

When it comes to your big data strategy, it helps to have a partner on your side that understands the inner workings of big data analytics and can assist you in executing the incorporation of all of your key insights into the decision-making process. This is where the experts at Data Realty come in. We can help you improve your relationship with big data and use it to increase the effectiveness of your decisions - no matter what vertical your company operates within, we can help you harness the power of your data.

Get in touch with the big data experts at Data Realty today for more information.