I’m often asked how someone who is a consultant how they can get into Big Data. This is an important subject because it will define your success as consultant in the field. More importantly, it will define how successful your customers will be.
If Big Data is brand new to you, learning should be your first and foremost concern. This is the one variable that determines your success or failure.
Let me give you an example of why. I’m often brought in by companies to oversee or check over Big Data teams. Sometimes those teams are made up of, or augmented, by outside consults.
At one company is was introduced to their consultants their Big Data experts. In talking to their Big Data experts, they told me how excited they are to learn about Big Data. Their experts are just beginners too!
Needless to say, everything those experts had done was wrong or beginner-level. They could answer my most basic questions about the architecture or design and looked terrible in front of their clients.
Remember that Big Data is complex. A group of beginners don’t equal one expert; they equal less than one beginner. If you come in as a beginner and mess up a a company’s project, they will remember that failure. You won’t be working with that company again.
Some of my students went into Big Data consulting. They’ve told how they’ve gotten contracts solely because of how much they know about the ecosystem. My students aren’t just coming away with begginer knowlege. Rather, they’re getting advanced skills and knowledge about the whole Big Data ecosystem. This is what clients want and they’ll pay for.
One of the most common routes I see is to get certified. These certifications represent a wide gamut of technical ability.
Some certifications are based on completing a course. These simply mean that you’ve through a, usually introductory, course for the entire time. It doesn’t show any specific abilities or skills.
On the high end, you certifications that are proctored (monitored by a live person) to see that you are the one doing the certification. These certifications also require a hands on portion that shows specific skills and abilities.
If you do go the certification route, pay the extra time and money. Get a proctored certification. Just know that unless your certification has a lot of cache, you will still need to explain your qualifications to prospective customers. Getting certified does not make you an instant expert.
Getting that First Client
After learning, your next step will be to get your first client.
This is an area where a good reputation is vital. If your client trusts you, they will look to you and trust you when you say you have Big Data skills now.
If you’re just starting out or lack the trust/reputation, you will need to prove your skills. As I mentioned a certification may help. I’ve found the best way to show skills is with an awesome personal project. I talk about personal projects in The Ultimate Guide to Switching Careers to Big Data and have an entire chapter dedicated to this on my Professional Data Engineering course.
When you’re consulting an awesome personal project is really helpful.
If you’re a consultant, you usually can’t show your project to other potential customers. With a personal project, you can show everything running and walk them through it. Ideally, this is something you can show on your laptop or running in the cloud. If you can’t make something run or it continually fails, how are you going to make something that works for your client?
You almost never can show them the code from previous projects. With a personal project, you own the code. This code is ideally up on GitHub. It shows your excellent comments, good organization, and professional prowess. If it doesn’t, go back and make sure it does.
Done right, an awesome personal project is the ultimate business card. After getting your first few clients, you reputation will spread and things will get a lot easier. You can join my other students who are successful Big Data consultants, but you’ll need everything I’ve talked about on this post to do it right.