Some organizations are investing billions in big data, but are not seeing any benefits. Big data is not really big if it is not beneficial to the company. Many organizations fail because they give more importance to massive data rather than the efforts that will help them realize their business goals.
The following are some of the big mistakes that you should avoid when dealing with huge volumes of data.
1. Focusing on numbers only. Big numbers are only useful if they contribute to realizing your business objectives.
2. Thinking that big tools symbolize strong data management. Apart from big tools, effective data management requires a corporate commitment.
3. Having a defined plan. There is no definite way of getting big data. The rules are dynamic and no single formula applies to all.
4. Assuming big data requires big leaps. A journey of a thousand miles begins with a single step. Take small steps that will enable you to reach your goals. It does not matter how many small steps you will take.
5. Looking at mass data as a project that is done once and completed. Data management is an ongoing process and there is no specific end point.
6. Making data management a side job. Allocate an IT team to be fully dedicated to data duties. Do not wait until you have time because you will never get time unless you create it.
7. Working on a whole basket of data. Choose only data that is important and useful at a particular time.
8. Making decisions based on big data. Do not let large volumes of data overcome your sense of judgment. Mass data should not be the determining factor for all decisions but rather contribute to it.
Both the company top executives and employees can get overwhelmed by mass data. This can in turn make them lose focus on the main goal of the project as they concentrate on managing the enormous data. To benefit from mass data, you should concentrate more on implementing business strategies and doing what matters.
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