Big Data Integration: Five Biggest Pitfalls to Avoid

Five Biggest Pitfalls to Avoid

The big data revolution has captivated a global audience on the promise of better decision making capabilities, improved customer engagement, and higher profits. From the healthcare field to the retail sector, the success stories are mounting. What you rarely hear about, though, are the stories of companies that have jumped on the bandwagon, yet failed to gain traction or fell off completely. When it comes to big data integration, there are some pitfalls that can sink your project to the abyss of no return.

1. Going At Big Data Alone

Some of the best big data tools are completely free to use, like the popular open source software Hadoop. But while organizations are free to deploy these apps on their own, that doesn’t necessarily mean they should. Hadoop alone will challenge IT’s ability to stay on top of monitoring, security, and day to day administration. The technical hurdles make for all the more reason to choose an enterprise big data solution backed by a credible vendor. This sort of investment delivers tools needed to streamline business operations as well as the support necessary to address problems as they arise.

2. Using Outdated Data Management Practices

It is not uncommon for businesses to view big data as an extension of their existing data handling strategy. This is understandable when considering that companies want to make the most of their investments and maximize technology that still works. Unfortunately, some traditional data warehouse architectures are so outdated that they actually limit the potential of data when integrated with more advanced systems. Modern big data platforms offer the ability to process information in real-time with a level of speed and efficiency many older tools can’t keep up with.

3. Ignoring Big Data Best Practices

While the term big data was just recently coined in the digital age, the concept and what it stands for is not new. In fact, there is already set of established guidelines that dictate what to do, and what not to do as far as this trend is concerned. One of the most known standards tells us to be selective in where we focus our energy because not all data is good data. Whether it’s choosing the right vendor or assembling the right team behind the scenes, adhering to big data best practices is essential to positive outcomes.

4. Failing to Understand the Importance of Big Data Governance

Realzing that not all data is created equal ties into the importance of governance. Organizations that understand the value here take the time to profile their data in order to gain a crystal clear idea on how it will be used, who should be handling it, how long it should be retained, and so forth. Data that lacks governance offers limited value to the analytical process and the business itself. Properly governed data is accurate, secure, ready to put into play, and as a result, immensely valuable.

5. Underestimating the Power of Big Data

Hadoop is more than a novelty data processing system. Likewise, NoSQL isn’t merely another open source database concept. The icons of big data are powerful tools that allow not just the enterprise, but companies of all sizes to process, manage, and store enormous volumes of information at a scale that eliminates the need to make additional investments in hardware. At the end of the day, failing to maximize their potential may very well be the biggest big data mistake you can make.

Big Data Integration: Five Biggest Pitfalls to Avoid
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