How to avoid Mistakes in Big data Implementation

Author: 
Selwyn Zhou

Big Data solutions can leverage enterprise data to build market share, develop more responsive systems, and conduct more effective research, among other things. But a cold hard fact is that over 55 percent of big data projects are not completed, and many more fail to meet their objectives according to a recent survey.

This indicates that it is not so easy to complete a big data project successfully. Here we offer some tips to help you to avoid some common conceptual mistakes.

SUCCESSS FACTORS

Data is very, very important but data does not mean everything.

We must admit that data plays a very important role, sometimes even the key role, in a project. But please never think that you will have a successful implementation if you have a clean, beautiful data pool. Ask yourself if your team is ready to handle other problems, such as budget , project duration, security and so on.

Human is always the X factor.

The “”win-win” model consists of two parts - the consultants and the clients. Finding the appropriate people on both sides is a guarantee for the project. Also, a terrible relationship between two sides will ruin an implementation.

Technology is only a tool rather than a destination.

Technicians have a natural proclivity to recommend the most advanced technology to the clients. However, focusing on the technology will mislead the project. We must remember that technology is only a tool to serve the clients. Our goal is to help the clients company to achieve its goals rather than make the project an advanced technologies showcase.

In order for you to benefit from hard-won experience, we have prepared a FREE eBook, "Top 10 Best Practices for Big Data Implementations", which you can get by pressing the button.

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