Thursday, Jan 21 2016

7 Tips to Structure Your Data Team the Right Way

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7 Tips to Structure Your Data Team the Right Way

The challenges of big data projects aren't limited to dealing with the structure of the data; the first challenge you face is determining the structure of the data team. Deciding the goal of your data projects is key to making sure you staff the team with the right skills to accomplish your purpose. Here are seven tips to help you staff and structure your data team.

Hire based on needs, not skills.

There's lots of buzz around Hadoop, but not all big data projects need Hadoop skills. Don't let keywords dictate your hiring; focus on the problem you need to solve and hire the specific skills required.

Be flexible.

Big data projects are new and the technology is still changing rapidly. You shouldn't expect the structure you put in place now to work for you next year. Anticipate rethinking your data team's structure frequently to keep up with changes in the industry and changes in your own organization.

Bring in multiple skill sets.

Data projects require technical skills for loading and managing the data as well as analytical skills to develop insights from the data. You should plan to hire engineers as well as analysts to make sure people can focus on the tasks they're most suited for.

Start with good data.

It's difficult to find value in messy, dirty data. You should expect data projects will need to spend time manipulating and cleaning data before the analysis begins, so take the time and staff needed for that task into consideration as you plan your team. It's likely you'll need more time and people to work on the data cleaning aspects than the analysis.

Use consultants wisely.

You may want to use consultants if it takes too long to find permanent employees with the skills you need, but you'll need to get the skills in-house eventually. If you have trouble finding the skills you need, consider training your existing staff. Consultants can help guide your team as they learn and transfer expertise.

Interview carefully.

Because big data is such a hot topic now, many candidates with limited experience are putting big data skills and projects on their resumes. Ask probing interview questions to find out the reality behind the experience they claim.

Hang on to your employees.

Because the data job market is so hot, you have to work to retain the skilled big data employees already on board. Make sure they don't get bored; offer them interesting challenges to solve, and pay market rates to keep them content.