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Key Reasons Big Data Projects Fail

Published on 25 November 15
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Key Reasons Big Data Projects Fail - Image 1
Big data is your information catalog that will not just help you understand the current happenings, but also help you predict the future. Big data projects help businesses attain newer goals. IT companies have started undertaking big data projects. Sadly, despite the large number of projects being instated in this direction, only a few have seen success. Failure can prove to be frustrating to the companies that have initiated these projects.

Questions like how or when big data should be used still remain unanswered, leading to major unawareness in this field. Many businesses commit major mistakes when working on big data projects. Here are few reasons that will help understand why big data projects fail.

Not Setting Project/Business Goals

When working on a big data project, you should establish the business goals. Most businesses walk into the big data world just because others are doing it. It is more of a herd mentality, which is one of the reasons why such projects fail. What is the reason for using big data? That question needs to be answered. What is the problem you need a solution to? A clear vision and even clearer goal is essential for big data projects.

Not Using Specific Technology

You should use the technology that will help you unleash the true potential of big data. If you just use the conventional technology or methods for big data, you may end up with wrong results. This is probably why technology plays an important role in big data projects.

Lacking Essential Skills

Does the team you have assigned for big data hold the necessary skills? If you have undertaken a project in big data, and donât have the necessary expertise, you might leave out a huge gap which will lead to failure during project execution. You will need to find the right employees with the essential skills to lead you towards project success.

Not Thinking Beyond Data

Data analysis is just a part of big data project. Accessing and processing data is obviously the key to a big data project. But, the key is to think beyond data. Network, personnel etc. are key to data analysis and success of big data projects. It is not just the data or the numbers, but a predictive report of how the numbers and data will help the companies achieve the success. It needs the human touch for success.

Not Strategizing

When you fail to plan, you conduct the project haphazardly. You will start and end without realizing what it is that you need to do or achieve. This unplanned execution causes failure of your big data projects.

Conclusion

It is not just the availability of data that matters in a big data project. You need to plan the whole analysis and execution of the project to achieve the goals established. Semaphore Software offers big data solutions to meet your business requirements and end goals.

Source [Apsense]





























Key Reasons Big Data Projects Fail - Image 1

Big data is your information catalog that will not just help you understand the current happenings, but also help you predict the future. Big data projects help businesses attain newer goals. IT companies have started undertaking big data projects. Sadly, despite the large number of projects being instated in this direction, only a few have seen success. Failure can prove to be frustrating to the companies that have initiated these projects.

Questions like how or when big data should be used still remain unanswered, leading to major unawareness in this field. Many businesses commit major mistakes when working on big data projects. Here are few reasons that will help understand why big data projects fail.

Not Setting Project/Business Goals

When working on a big data project, you should establish the business goals. Most businesses walk into the big data world just because others are doing it. It is more of a herd mentality, which is one of the reasons why such projects fail. What is the reason for using big data? That question needs to be answered. What is the problem you need a solution to? A clear vision and even clearer goal is essential for big data projects.

Not Using Specific Technology

You should use the technology that will help you unleash the true potential of big data. If you just use the conventional technology or methods for big data, you may end up with wrong results. This is probably why technology plays an important role in big data projects.

Lacking Essential Skills

Does the team you have assigned for big data hold the necessary skills? If you have undertaken a project in big data, and donât have the necessary expertise, you might leave out a huge gap which will lead to failure during project execution. You will need to find the right employees with the essential skills to lead you towards project success.

Not Thinking Beyond Data

Data analysis is just a part of big data project. Accessing and processing data is obviously the key to a big data project. But, the key is to think beyond data. Network, personnel etc. are key to data analysis and success of big data projects. It is not just the data or the numbers, but a predictive report of how the numbers and data will help the companies achieve the success. It needs the human touch for success.

Not Strategizing

When you fail to plan, you conduct the project haphazardly. You will start and end without realizing what it is that you need to do or achieve. This unplanned execution causes failure of your big data projects.

Conclusion

It is not just the availability of data that matters in a big data project. You need to plan the whole analysis and execution of the project to achieve the goals established. Semaphore Software offers big data solutions to meet your business requirements and end goals.

Source [Apsense]

This blog is listed under Data & Information Management Community

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