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5 Tips for Making the Most Out of Your Hadoop Project

If you’ve been studying up on how to launch a big data initiative, Hadoop has probably stood out as a viable, affordable and manageable way to begin. In fact, Hadoop is a great option, and affords a tremendous amount of accuracy, insight, and predictive power for those willing to undertake it. That said, adopting Hadoop isn’t a cake walk. There are several tips for assuring that your Hadoop big data initiative gets off to a promising start.

1. Chose One Specific Goal to Begin With

Determine the one project you most want to get done with Hadoop. See that one through before taking on any others.

It’s really easy to get caught up in the potential for Hadoop and let your startup efforts get derailed for lack of focus. Decide on a single, specific goal, and concentrate your efforts on that particular goal. During your first Hadoop project, you’ll learn a lot that will be tremendously helpful with additional projects, but trying to take on too much at once is a recipe for failure. There might be tons of uses for Hadoop over time, but your beginning efforts should be targeted and focused until that steep learning curve is conquered.

2. Stop Tossing Potentially Useful Data

There is usually a lot of data being tossed out within an organization that, over time, could yield tremendous insight with big data analytics. Just because you don’t recognize an immediate need for raw, unstructured, seemingly useless data doesn’t mean that it couldn’t hold potential once you get a handle on Hadoop operations.

If big data analytics is in your organization’s future (and it should be!), start hanging on to all the data you can get, including semi-structured and unstructured data (like Word documents, emails, and PowerPoint presentations). It will likely pay off significant dividends in the long run.

3. Start Small and Leave Room to Grow

Your Hadoop operations don’t have to be fully mature before you get started. Start little and leave yourself room to grow.

There is no need to budget for, purchase, or set up a huge infrastructure for Hadoop in the beginning. This is the mistake that leads many organizations to outlay lots of money before Hadoop has yielded its first valuable insight. The beauty of Hadoop clusters is that the infrastructure is expandable. Start with only what you need to undertake your first Hadoop project, and build it as your understanding, plans, and insights grow.

4. Recognize That Maintenance is Part of the Game

While the cloud is always a viable option for Hadoop, many businesses are housing Hadoop operations in-house, along with their mainframe and existing IT infrastructure. That allows for optimal security and control, but also amounts to a lot of housekeeping in terms of maintaining, servicing, and budgeting for inevitable equipment failures. The average IT department can figure on about 5 to 8 percent equipment failures per year. Budget and plan for this so that normal equipment malfunctions don’t derail your Hadoop operations or drive them way over budget.

5. Be Flexible in Your Outlook on Big Data Analytics

It is rare that insights and perspectives derived from big data analytics are what they were expected to be. The data simply surprises you. This means that you can’t box in your Hadoop endeavors from the start, or even after you’ve gotten a handle on it. Be flexible and allow the data to tell you what you weren’t expecting to hear. This puts you in the greatest position for leveraging all that analytical power.

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