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Three Steps to Take for a More Successful Data Analytics Project

Organizations use data analytics because it uncovers unique insights that can help solve a multitude of problems; anything from improving customer retention to risk management. Not taking the time to set yourself up for success, however, can cause your data analytics project to be rife with headaches. Here are three steps to take for a more successful data analytics project.

Incorporate the Entire Business in the Kick-off Discussions

The planning stage is the most important part of any data analytics project, so you need to make sure you get the right people involved. I’ve seen it time and time again where the IT team tries to handle the project by themselves, but ultimately that leaves entire departments starving for the real data they need. Get several department heads involved, depending on what your business structure looks like, but don’t worry about interpreting all of the data at once. It may take several steps to get everyone’s information represented, so start with one department’s needs to ensure you can feasibly present it before adding in more.

Carefully Consider Your Platform Choice

Choosing the right platform in which to store your data is an important decision and is unique to each organization. How much data do you have? How much do you want to spend? If affordability is an important factor, maybe you can build it on something you already own, such as SQL Server, MySQL or Oracle. If you’re considering this, you’ll want to do a proof of concept so you know whether the platform is feasible, whether it can scale as necessary, or if another platform would be a better choice. Some organizations look at a proof of concept as a waste of time, but it truly isn’t. In vetting your platform choice you’ll have already thought through a lot of what can go wrong along the way. Many companies are eager to buy the latest and greatest technology, but that typically comes with a huge learning curve which will slow the process down. There are pros and cons to any platform, so it’s important to dedicate time to your decision.

Standardize Your Reporting

With multiple people and departments involved on a data analytics project, you’ll want to make sure that you standardize your reporting ahead of time to avoid confusion. Creating some sort of standard view, stored procedure or code that everybody uses when they’re reporting on the project will help immensely. For example, let’s say that someone asks to see sales for the month of April, but the business rule states that a sale only counts if the bill is paid in full. Not consistently incorporating this business rule will cause confusion and inaccurate reporting. Having an organizational data dictionary which explains these standardizations through examples can help to reduce confusion and surface any gaps.

If you’re eager to make use of the vast amount of data within your organization, consider these tips to avoid the aggravations that can occur on a data analytics project. By taking the time to think proactively about the most important aspects of the project, you’ll be able to deliver an end result that will provide powerful insights about your business.

About the Author:

Karen Murphy is a Senior Consultant based in our Fort Wayne Development Center. She’s been working in technology for 25 years, having served in various roles and industries including financial services, transportation, manufacturing and healthcare. When she’s not working, Karen enjoys cycling, softball and the great outdoors.

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