Three Steps for Building a Big Data Dream Team

May 31, 2016 0

In the ever-changing technology environment that we currently live in, it can be easy to get bogged down, both on the personal level and business level, trying to figure out how you can best implement the latest releases. Whether it’s a new phone or tablet or new Big Data software, it’s easy to get stuck.

For a company to succeed it’s got to figure out how it can leverage it’s current business position and products with the new Big Data platforms that are available. A sound understanding of how the technology can improve your product and your offerings is a must before actually going with the technology.

Because of all the hype that surrounds every new technology release, it can be easy to get caught up in the euphoria of the moment and immediately hop on the bandwagon with no real purpose or direction with what you’re doing.

This is especially true with Big Data. In many respects Big Data is extremely complex and difficult to understand, at least the technical aspects, by someone who comes from a non-data background.

All too often a CEO will hear of the abilities Big Data has and naturally, want to implement it into his or her business operations. The problem, however, is that the company doesn’t have the right talent, the right culture, the right understanding and, possibly, the right technology to really make the most of Big Data.

When it comes to getting up and running with Big Data in your company and building your own dream team there are certain steps that need to be taken to ensure complete success.

1. Data needs to be a priority

If a company is going to succeed with Big Data, the entire company has to buy into the Big Data concept — from top to bottom. Otherwise, people will get undercut, initiatives will get derailed, executives will clash and Big Data will go from help to hinderance very quickly.

The CEO sets the example and should expect everyone to follow. And while most CEO’s aren’t going to come from data backgrounds, that’s ok. It’s not necessarily understanding the technical aspects that matter. It’s clearly understanding what the technology can do for the company.

2. Implement the right technology

Big Data in the cloud is completely changing the availability and affordability of Big Data. In so many ways it’s making Big Data a real possibility for companies of all sizes. There’s no expensive infrastructure to install, no servers to maintain, no expensive startup costs and much more flexibility.

Additionally, cloud computing completely changes how CEO’s look at building a data team.  A Big Data in the cloud provider, does so much of the work on the data end that the companies don’t have to worry as much about hiring large data teams full of individuals with advanced degrees in data science.  What companies now have to worry about is hiring the right people.

3. Hire the right people

So, who are the right people? The right people come from any background, but they have a sound understanding of the importance of data and how it can help the company. Your business needs to find talented individuals who can find innovative ways to implement technology to solve your most difficult business solutions.

They don’t have to understand exactly how the technology works, but they must understand how it can benefit you. Obviously, hiring the right people makes all the difference.

It’s tempting to want to hire a large team of data scientists, but with Big Data in the cloud that’s not what you need. The cloud service providers already have that team of scientists. If you hire more, it’s only going to make things more difficult. To succeed, the company needs smarts on how to best use the technology, starting with the CEO and going down.

In today’s business environment, it’s more important than ever that companies get their data strategies right. A Big Data dream team takes time to assemble, but it’s worth every minute and every penny. Remember it’s understanding how technology can work for your company that will make all the difference.

Categories: Big Data

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