In a survey of our customers who are using Big Data for analytics, we found clients who love it and some that don’t. These clients are having struggles that are leading them to thoughts of abandoning it. In this edition of Azure Every Day, I want to share a few of these challenges so you can identify them in your environment and hopefully avoid them.
1. Big Data Analytics is not flexible, fast or accessible.
Creating a Big Data environment is technologically advanced, and often organizations struggle with usage and performance. Updating the environment solved a technology problem, but not a business problem.
Keep in mind that the reason we use analytics, Big Data or cloud service technology is to make it more accessible, fast and flexible. If you’re not achieving these goals, step back and look at how you are approaching achieving them.
2. It’s not meeting the business goals.
So, the cluster is processing, jobs are running and you’re making predictions, but the business is not connected to that data. Maybe you’re not analyzing enough data or your teams can’t get to that data with a tool like Power BI, for example. Be sure your business feels like they are part of the process and that they are connecting that data. Otherwise, it won’t meet your business goals.
3. Make sure your audience is appropriate.
Once the business is part of the process, be sure your audience is appropriate. If you say you’re using Big Data analytics to run your business, but you only use it to help a narrow audience (manufacturing analytics for example), the rest of the company will not get the same level of buy in. It’s ok to start small in one department, but be sure to build and grow your audience for that type of data and analysis.
4. What are people going to do when they get the data?
Is your team data literate? Do they know how to access and analyze the data or know what to do with it? Your analysts and managers need to know how to do this. You may need to make an investment for your team to be able to work with all the great technology and analytics that you are providing.
The bottom line is, yes, it can be a little tricky to pull this all together and make your Big Data analytics project a success for your business. Pragmatic Works has helped over 7,000 customers world-wide with our proven strategy to solve these problems and help lead you to success.
Click the link below to learn more or contact us to set up a time to speak to one of our architects to see how we can work together with you and your team to avoid these pitfalls and make your Big Data analytics dream a reality.