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Why Most Big Data Projects Fail + How to Make Yours Succeed - Page 2

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Start with a list of questions and business problems you want to answer

Don’t tackle something huge. Start with a small project, make it about a specific issue you need to address and stick with it. Make a list of the questions you need to answer, and don’t lose sight of your objective by getting stuck on making the technology work. Keep your team from becoming too broad or all-encompassing, so you can avoid scope creep and its project failure button: a constantly changing set of requirements flowing from the business to IT. Make sure all stakeholders agree on the objective and keep everyone focused on driving it to completion.

Get endorsement from the top before you start

Once you have identified the business problem you want to solve, the business team must have endorsement from the top down to get access to all the data needed to complete the project successfully. Get company leadership on board with granting the team access to all relevant business data, so they can find the patterns and relationships that will answer the business questions. They must be given access — controlled, of course — but with authority.

Make sure your team has the knowledge necessary to execute the project

Ideally, you will have someone on your team who understands machine learning, has the skills and mindset of a data scientist and can actually work with the data to produce the needed business result. If not, you may be able to solve the problem with your existing system. This is a good time to again step back and consider the business questions you need to answer. You may be able to get the answers you need without machine learning or NLP, just by granting access to the right people inside the organization.

Choose a problem that creates value for the business, have the fortitude to stick with it and you’re already on the right path. And remember, a successful project is so regardless of its scope. Don’t set yourself up to fail by biting off a chunk that’s too big. After all, it’s better to succeed in a small project than to fail over and over on a grand scale.

Title image courtesy of extradeda (Shutterstock)

Editor's Note: To read more on how the enterprise is tackling big data, see Phil Kemelor's The Digital Analytics Center of Excellence Dream Team

About the Author

Darin Bartik is executive director of product management for Dell Software’s Information Management solutions.

 
 
 
 
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