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5 Big Data Mistakes to Avoid

Last update on April 14, 2016.

Big Data MistakesBig Data technology has fascinated businesses with its ability to forecast customer demands and business opportunities. More and more businesses are embracing this technology to extract value from the massive volumes of data that they generate every day, and if you’re one of them, this article is for you.

Investing in big data analytics is a great business decision, and to gain maximum benefit from your investment, you must use is the right way. In this article, we are listing the top 5 common mistakes that you should avoid in order to achieve your objectives of investing in this technology.

Mistake No.1: Not Having a Business Case

Big data analytics solutions and services can be expensive. To make your investment profitable, it is important that you have clear objectives in writing that you want to achieve with the big data solution. Also, make sure that these objectives are communicated to your service provider.

Mistake No. 2: Ignoring Data Relevance

Every business today generates and manages large volumes of structure, semi structured, and unstructured data. To get the most out of your big data solution, it is important that you make sure that the data you present is relevant and contains useful information.

For example, if you’re a call center business, you may exclude the phrase “the call may be recorded for quality purposes”, when converting your audio data into text based data.

Mistake No. 3: Providing Data of Poor Quality

The accuracy and completeness of analytics and forecasts depends on the quality of the data that is being analyzed. If you’re analyzing unstructured data, such as text, audio, images, or video, you may consider improving their quality through quality-enhancer tools.

Mistake No. 4: Not Preparing for the Change

Implementation of big data solution is a major technological change that your organization will experience. In order to make this transition seamless and profitable, it is important that you develop a strategy to improve data knowledge and domain knowledge of your employees.

Mistake No. 5: Taking Big Risks in the Beginning

The most common mistake made by enterprises is to implement a highly-advanced big data analytics solution when they first start investing in big data. Remember, the small firm steps in the beginning will help you move quickly in the long run. Therefore, begin with implementing a flexible big data solution, develop your expertise, and then move forward.

Knowing what not to do is extremely important in big data. So, watch out for these common mistakes and make your big data journey fruitful.


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