How to Capitalize on Big Data with IT Automation

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In this special guest feature, Jim Manias, Vice President at Advanced Systems Concepts, Inc., discusses how organizations can best capitalize on their data using IT automation. Jim is responsible for the overall market strategy and planning for a range of products including ActiveBatch Workload Automation and Job Scheduling. He has been with Advanced Systems Concepts since 1991 and has held multiple senior management positions in the enterprise software and hardware market.

Organizations are increasingly (and rightfully so) putting more emphasis on finding ways to better leverage their data, and investments in solutions that extract useable information from big data are rising accordingly. IDC estimated that the big data and analytics market jumped from $112 billion in 2015 to $150 billion in 2017, and projected that number to grow to $203 billion in 2020. The problem is, the investment isn’t paying off for everybody.

According to a recent survey by big data consultant NewVantage Partners, while 85 percent of companies have started programs to create data-driven cultures, only 37 percent have succeeded so far. As organizations are realizing, simply investing in the right big data tools and applications does not lead to positive results on its own. Companies have to be able to coordinate tools and applications in a way that makes them work together seamlessly, while also getting the data to the right people within an organization in a timely manner. This is where IT automation comes into play.

Breaking silos and integrating software

IT automation is defined as the linking of disparate systems and software – which includes big data tools and applications – to make them self-acting or self-regulating. This capability has become even more important as companies leverage a growing number of big data tools and applications that create an additional level of complexity. As described by business application research website, “The growing number of big data use cases and the adoption of new technologies go hand in hand. As a result, companies will soon face even more heterogeneous IT landscapes, which will create further challenges.”

When big data tools are not integrated into the larger IT architecture, these tools and applications are rendered useless outside of their immediate silo. However, with IT automation, companies can tear down these siloes, enabling them to leverage everything through one coordinated system.

Traditionally, companies use scripting to connect heterogeneous applications and systems that were not designed to work together. However, to reduce the need for the repetitive and error-prone process of scripting, IT automation solutions provide pre-built and tested logic so companies can focus on function, rather researching, writing code and testing workflows.

Transforming data into insights

At the end of the day, data is only as valuable as the insights it produces. Take the Hadoop ecosystem, for example. Companies often struggle to make the data produced from Hadoop applications available to other departments and applications in a timely manner. Analyst Joe McKendrick further explains, “If organizations go the Hadoop route, they need to consider how they will integrate the analytics created in the data lake with the operational systems that need to consume those analytics in real time.” This is where IT automation can make a big impact. It helps organizations by simplifying the plumbing required to incorporate data from Hadoop into workflows, so they can spend less time preparing and integrating data and more time analyzing it. Organizations can thereby achieve deeper insights from data while also leveraging it more quickly.

Without effective IT orchestration, data won’t get to the right people in time, reducing its value. The real benefits of big data are realized when better decisions can be made for the company and customer in real time. To make this a reality, it’s increasingly important that organizations fully capitalize on their big data tools and applications, as well as the data generated within them. While IT automation is only one piece of the puzzle in extracting value from data, it is certainly an important one.


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