5 Big Data Challenges (Plus Free Resources to Help)

Challenge 1: Figuring Out Your Big Data Use Cases

Why It’s a Challenge

If there’s one issue we hear over and over again, it’s the importance of determining the right business use cases. If you’re trying to prove the value of your program (and at some point, you’re going to have to), you need to start with some solid use cases in mind.

The problem is selecting the right use case. There are dozens, hundreds of use cases out there. But it’s best if you choose one where you can not only analyze data to find meaningful trends, but also work with the business teams to make an impact using your data.

Your data is going to have to prove its business value.

What Can You Do?

At Datameer, we’ve created a Use Case Browser with hundreds of real-life use cases. Filter through results to find ones that are suitable for your purposes.

Otherwise, download our free ebook on the top five most popular use cases we’ve seen.

With all this emphasis on how important it is to select a business use case, you might find yourself stressing about picking the perfect one. We say, don’t stress yourself out so much.

Why? We actually recommend that you pick out a few smaller use cases first. Smaller use cases mean it will also be faster to gain results and start demonstrating impact. This will give your team a morale boost and some quick wins to provide motivation as you begin your big data journey.

Challenge 2: Improving Your Agility to Get Answers Fast

Why It’s a Challenge

Organizations want to find answers fast so they can increase the speed at which they do business. Your agility will come from addressing five key challenges with big data analytics:

• Effective data management, with efficient management and retention of the right data to optimize storage and flow
• Dealing with data complexity and inaccuracy, with an effective curation process to tame the data and make it useful
• Enabling free-form discovery, with a self-service, data-first approach to exploration and discovery
• Controlling data without stifling innovation, with easily moderated access that keeps private data locked down
• Getting results to the business, which requires continuously running processes that feed data to the business

What Can You Do?

Well, first of all, we recommend a data lake. Simply building a data lake won’t give you the agility you want from your analytics. But building a data lake does provide a single repository of your organization’s data, whether it’s structured, unstructured, internal or external. This allows your business analysts and data scientists to potentially mine all of your organization’s data.

But there is a right way and a wrong way to build a data lake.

We’ve put together this ebook to help you build your data lake in a way that helps you gain maximum agility in getting answers faster.