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How To Tackle 6 Big Data Challenges

24 Jun 2015

Big data analytics maybe the newest kid on the block, but for a large number of industries, it has driven business value and augmented revenue. With ‘Internet of Things’, better connectivity among devices and increased acceptance of business analytics, companies can take advantage of the tremendous opportunities big data provides. While the expected benefits are vast, firms do face some roadblocks with big data. They are:


Issues with Big Data Adoption


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  1. Speed

  2. In today’s ultra-competitive business landscape, firms have to search for relevant data and process it faster. Visualization can help companies take faster decisions but the difficulty lies in examining through large volumes of data and drilling down to details – all at a very high pace. Hence, speed is one of the top challenges in big data analytics.

  3. Data Comprehension

  4. Apart from data determination, a broad understanding about the same is essential. It is important to get data in the right format so that the process of analyzing it is simplified. For example, when social media is the root of your data, you need to know who your user is and what is it that you are trying to get out of the information about that user. Without a context in place, the data is not valuable.

  5. Managing Quality of Data

  6. Locating the data and creating the proper context for the audience is not the end. Accuracy and timely availability of data is crucial for decision-making. Big data is only helpful when an information management process is implemented to guarantee data quality.

  7. Cross-functional Dependency Issues

  8. Big data activities often involve a variety of professionals. Frequent cross-functional interactions among finance, marketing, engineering, IT and production are likely. However, data ownership tends to get diluted across various divisions. Companies need to check whether all the functional units are on the same page about data analysis. Working across the business will help companies address these probable obstacles.

  9. Data Synchronization

  10. Despite the reported benefits of big data, the fact remains that data is spread through heterogeneous sources. It is a major project for companies to connect these data points and access untapped insights. At times, organizations may not have the correct platforms to capture this data and distribute it in the enterprise.

  11. Finding the Right Implementation Partner

  12. There are near constant evolutions in the IT world and specifically in data sciences industry. To leverage data effectively, it is important to partner with a strong and progressive technology partner. The right kind of partnership can enable your organization form an appropriate IT framework that can withstand landscape changes efficiently.

In conclusion, the challenges of big data described above show some of the aspects that need to be considered even before it is adopted in the enterprise. Developing a strategy to mitigate the data management risks outlined above will help you address any obstacles that may arise as you transition into being a Big Data oriented enterprise.

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