Bobby Koritala | October 22, 2015

Big data can take you off course without a proper data management and analytics framework

Businesses, governmental agencies, and individuals all around the world create data – and are doing so at an overwhelming rate. In fact, according to some sources, we’ve generated more than 90 percent of all of the data ever created in just the past two years.

While this may not be news to those of us who plan for, manage or process this ‘data deluge’ – questions still remain about best practices when taking on infrastructure changes to address big data in a big way.

Big data, without structure, can be, simply, noise – massive amounts of information emanating from a large, and growing, pool of internal and third-party sources. What was once a question of how do we get the data has evolved into a question of how to manage, analyze and operationalize insights from this data analysis.

Something I read the other day resonated with me: a TechRepublic article stated, “Data is the most mishandled and misunderstood IT resource, and it is compounding the issue of IT credibility.”

As expectations change for IT departments today, it is important for them to get data management right. If it isn’t doing so already, IT needs to wrap its head around big data – from start to finish – because it’s a 2.5 quintillion byte business opportunity that isn’t going away anytime soon.

The sheer volume and growing sources of data pose an abundant challenge to information technology leaders. IT leaders ready to meet this challenge must equip themselves with a plan – one that spans across the entire enterprise and breaks down the walls between departments.

IT must think bigger, obtain executive buy-in and consider system integration as the foundation for big data success.

Seems simple, right? So why isn’t it?

Don’t Let Bad Data Take You Off Course

Big data means that once small bad data problems now become magnified as big problems that can cause flaws with the very analytical results that were painted as one of the virtues of big data.

“Outside of security, data management and analytics, big data likely represents the biggest IT spend of most organizations…But the frantic way in which businesses want to consume, track and trend data is outpacing the ability for most organizations to do it right,” the TechRepublic article notes.

And it’s true; data integration and data quality are the top challenges companies need to overcome before embarking on analytics initiatives.

For this reason, bad data should be IT’s biggest enemy. Here’s why: In the land of big data, even small issues in data quality can create huge mistakes in decision making.

But data quality concerns don’t have to keep IT up at night. With automated, continuous controls and deductive analysis, IT can be confident that mistakes will be flagged and reconciled, and that the right people will be alerted to the issue to maintain good data across the board.

Automation should be a given. Consider a commercial airline cruising along from point A to point B: you might not realize they fly on autopilot most of the time once they are at altitude. At 30,000 feet and 500 miles per hour, small deviations driven by human error can mean the difference between landing at O’Hare and landing in Atlanta.

It’s better to automate that process and let machines do what machines do best.

Similarly, problems with data quality can take your business decisions off course. End-to-end deductive analysis of data can reduce risks by automating the process and in turn reducing the cost of ensuring quality data from the get go.

Like a pilot off course, bad data compounds in severity when organizations assume the data is trustworthy and apply it to data analytics when making decisions. When companies ignore bad data, at any stage, it can result in poor insights, misleading interpretations and off-the-mark outcomes. As they say, garbage in, garbage out – or, in this case, “landing at the wrong airport.”

Ensuring data reliability needs to be the first step in putting big data into action. However, automated, integrated data quality solutions can help IT keep their organization on a true heading, getting your business to the right destination each time.

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