Common Reasons Why Big Data Projects Fail
Data scientists believe that big data is the next big thing. Big data promises to solve customer service conundrums that have been perplexing businesses for decades. Many businesses are already using it to improve their customer service.
Over the years, several businesses have launched big data projects, and not all of them have been successful. Big data is a relatively new concept, and not many companies are well-versed on the topic. This, however, does not mean you necessarily have to put your idea on the backburner.
Once you come up with your big data strategy, you need to watch out for common mistakes in order to achieve your project goals. So what are these mistakes? Let’s take a look.
- Lack of a skilled team
You need a skilled and efficient team comprising of experienced engineers, data scientists, and IT support personnel to implement Big Data successfully.
In addition to possessing the skills and knowledge required for the job, these professionals must be aware of how the business operates. They should be qualified to ask the right questions and capable of visualizing various possibilities.
- Improper data structure
Oftentimes, businesses receive data clusters in improper data formats. Teams working on the project have to spend a considerable amount of time arranging data into a usable format. Additionally, many companies store data on local servers, which results in the formation of data silos. To avoid this situation, businesses must come up with a strategy to identify and structure data in the early stages.
- Resistance from the management
Big data projects are involved projects. Their implementation requires a significant commitment of resources. No wonder in many cases the management is unable to understand the long-term benefits of big data implementation, which results in friction between the project team and the top management. If you are unable to get your management and project teams on the same page, be warned that your project is a disaster in the making.
- Poor planning
Someone rightly said that failing to plan is planning to fail. In their eagerness to jump on the big data bandwagon, many businesses fail to set goals and answer important questions. To get the most out of their big data projects, businesses need to plan ahead of time and prepare for challenges. Before committing, the firm needs to define the problem and must also seek answers to important questions, such as why they must solve the problem and how big data will help.
At iMovo we can give you advice on your big data project and implement a visual data analytics platform which will allow you to harness the power of your data. Particularly in such an industry where every second counts, a big data analytics platform can help you connect and visualize your data in a timely manner. We will also support you throughout the whole journey. For more information contact us on [email protected].