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Hadoop and IoT: Three Things CIOs Need to Know to Succeed

Umair Khan, Principal Product Manager ,CA Technologies and Beeshmanth Kotamreddy, Principal Product Manager, CA Technologies
Umair Khan, Principal Product Manager ,CA Technologies

Umair Khan, Principal Product Manager ,CA Technologies

For many of us, the idea of a Jetsons-esque connected world has been little more than a pipe dream over the past several decades. But now that dream is quickly becoming a reality, as the Internet of Things looks set to hit escape velocity in 2016 and beyond.

“Market opportunity for big data technologies and services will grow to nearly $41 billion by 2018. And a huge part of this opportunity will be owned by Hadoop”

Yet with the IoT rapidly growing and becoming a normal part of our day-to-day lives, the amount of data that is now being transmitted and collected is unprecedented in human history. In fact, according to CA Technologies, the market opportunity for big data technologies and services will grow to nearly $41 billion by 2018. And a huge part of this opportunity will be owned by Hadoop.

Hadoop’s value is in sifting through this explosion in big data. But, without a unified management strategy that unifies traditional IT and Hadoop infrastructure together, companies will not be able to succeed at interpreting and utilizing this mass of new data. Here are three tips to help CIOs understand the role of Hadoop and how to best implement it across the enterprise.

The Value of Hadoop: From IT to Customer-Facing Applications

Advertisers and marketers are the most obvious organizations that will need big data analytics tools in order to handle the growing volume of data resulting from IoT. But these big data IT concerns are not limited to any one specific industry – CIOs from banks to retailers to healthcare need to understand the importance of analytics and how to properly implement analytics strategies across their businesses. For example, a large retailer utilizes point of sale data from hundreds of locations to manage their store inventory. They’ve automated the overall process which taps into Hadoop (for big data inventory analysis), then moves into different fulfillment and inventory systems so that the right products show up on the right shelves. The operational components are fully automated and it ties both Hadoop and non-Hadoop processes together to fulfill a business need using big data.

The need for a unified IT & Hadoop strategy doesn’t just affect internal IT operations within an organization, either. Customer-facing applications have heightened the need for these strategies. In the past, companies could afford to keep their data analytics infrastructure in a silo because the information derived from it was largely internal-facing. But customer-facing applications and services, such as shopping apps that provide real-time recommendations, are increasingly utilizing these analytics.

If there isn’t a unified set of tools and protocols in place across your enterprise, it could have a direct impact on your bottom line. The proliferation of big data means that IT teams and analytics departments need to be able to scale, and quickly. If there isn’t a unified view, architecture and strategy across the enterprise, scaling up becomes exponentially more difficult and can negatively affect a company’s performance no matter the industry.

How Can CIOs Successfully Navigate This Big Data Landscape?

As you’ve already noticed, there’s a running theme here: unity and standardization in your organizational IT and Hadoop strategies is crucial to success. But how does a CIO coordinate this ideal strategy? Here are a few pointers that CIOs can follow that can make their lives exponentially easier: Beeshmanth Kotamreddy, Principal Product Manager, CA Technologies

• Be a student of big data: Big data analytics as a category is maturing, and so are the vendor solutions and services available. To add to the complexity, “big data analytics” means something completely different based on your organization’s need. Consider contacting industry analysts to help guide your next steps, as well as peers who have tested the Hadoop waters. The bottom line here is that CIOs must understand that since this is a constantly changing arena, it’s critical to have that state of mind when rolling out any related initiatives.

• Embrace automation: When you’re trying to ensure a unified implementation across multiple business teams, automation across job processes can be a life-saver for a CIO. The less you need to manually monitor and manage: lesser chances are there for mistakes to be made. This also allows you to keep your managing teams to more manageable sizes, allowing for better training and skill-specialization within the teams that are responsible for these Hadoop-relevant technologies and processes.

• Siloes are the enemy: If Hadoop had an evil arch nemesis it would be an organizational silo – in order for a Hadoop strategy to succeed, information and structural silos must be avoided. Managing the amount of data that is being provided by the IoT is hard enough as it is. Having a fractured IT organization will only make that tougher, if not impossible.

Collaboration, unity and understanding of the tools available are hardly the most profound pointers to give to the CIO of an organization. But when dealing with something as new as the explosion of big data resulting from the IoT, it can be very easy for organizations to get “wrapped around the axles” when implementing their Hadoop analytics strategies. Once that happens, even the simplest goal, like standardization across IT teams, can become lost as new questions pop-up to supplement the ones that you are already trying to solve. Hadoop and big data analytics is complex stuff. But by keeping the focus on collaboration, unity and constantly updating the organization with the latest and greatest information on the technology trends, today’s CIOs can be better equipped to tackle the opportunity that is big data.

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