Many people change direction in their careers. Some of us would call that growth.
When something grows, it usually builds a healthy base from the ground up before it blossoms. The positions for people that participate in data science are part of that healthy base. However, there is an issue – we have a massive shortfall in human capital. You can’t have the data and no people to work with it. We have to have people who know how to use the tools used to manage data and analyze data.
The roles in data will evolve as technology and tools on data advance.
Imagine that what’s growing is a tree. Every branch has an end, but the tree continues to grow branches. When the tree reaches maturity it becomes the tree that it’s going to be and just blooms in cycle. Just like a world with no trees, the world with no one to fill the roles of data is a terrible place.
The jobs are coming but they maybe their companies aren’t invented yet. This is to your advantage.
There are lots of jobs already in the market unfilled but as more and more companies get control of managing their data, and more companies are invented or reinvented, more jobs will be created. We didn’t need metal workers until we realized how much metal we have. This means you have time to prepare if you already have a job/career.
How do you know if you should consider data as your future “skill” choice?
Consider training that has been thoughtfully laid out to meet the economic short falls in education for the data workers. If any of this interests you, then dig deeper into the topic and see where it takes you.
Don’t get discouraged. Everybody starts from a different point.
In the field of data science I know this to be true. If you don’t build your base, then starting at R is discouraging. Remember that you may be at the beginning of your journey, or you might discover you’re actually in the middle. Never forget the path for your data career is as diverse as the data you’ll encounter.
Recommended Training for the Fundamentals
This list has been prepared for you to get started. It’s great for anyone, no matter where they are, to have a review and get into technology related training for self-growth. Remember, you are a tree with branches.
This is one of my most favorite clips: http://bit.ly/ThreeTruths from my course “The Basics of Data for Analytics.” I think anyone who reads, requests or writes reports should understand this concept. If you are currently an analyst look at http://bit.ly/InterpretResultsOfData from Curt Frye’s course.
If you have already started down the data road and currently work with lots of data then you either already know this or you need too, watch http://bit.ly/JOINS. (This video you can watch without subscription). If you know this concept but don’t understand what to do with those ugly NULLs, then watch http://bit.ly/RemoveUglyNulls.
The hypothesis might exist or might not when you start on a project. Curt Frye’s Course on “Data-Analysis Fundamentals with Excel” has a segment on the hypothesis as it relates to data analysis. Great segment for you to watch either to confirm you know it already because you need to know it. http://bit.ly/learndatahypothesis