Here’s something funny to think about. In a field that prides itself on being “data driven”, why is it then that a great majority of self-proposed thought leaders and talking heads all have different opinions on the topic of analytics?


I’m sorry to break this to you but there are many people out there that just don’t have a clue of what they are talking about. It pains me because I am constantly talking to those who are very eager and want to get into this field and yet when you Google “How to get started in Analytics” or see articles published in LinkedIn you are told very different stories. It’s not right or frankly fair to you. We need all the help we can get in Analytics and we shouldn’t be making it harder.

So here is my attempt to make it a bit easier for you. I have listed what I believe are truths in getting started in Analytics. There will be some that disagree, great! If you do then say so in the comments below. I couldn’t be in analytics and not welcome different points of view. Just remember….

[bctt tweet=”Soap boxes are good, High horses are not”]

Analytics Truth #1: Analytics is not hard.

So many make it seem like you can’t get started without a PhD in statistics and it’s simply just not true. Is it helpful to be trained in a quantitative field such as mathematics, physics, statistics, or other sciences? Of course but it’s not required to get started.

  • The magic of analytics is about solving problems, if you can do that and even do it well you will do fine. I’ve seen people who can’t sit still to save their lives but can out think and solve really complex problems better than many PhDs any day.
  • Analytics is not hard because it’s not only about the math. I solve a grand majority of problems on the whiteboard, while talking through with others. Only once I have most of the clarity and understanding I need do I “code” it. Again if you are just trying to get started, focus on solving problems. You do Analytics in the process of solving problems and there is no commandment that you have to use math to solve the problem.
  • How about you just try good old brain work and think/talk through the problem. You’ll be amazed at what you can come up with.

Analytics Truth #2: Experience trumps Education

If you want to get into Analytics don’t put all your eggs in the education basket. Focus more on doing things (read: solving problems). Learning is great and don’t stop but in the mindset of trying to get a job in Analytics focus on what you can do with the education. So many people take all the coursera or edX courses they can and then think they are ready to go….not quite.

  • For every new technique or topic you learn find 5-10 ways you can use it to solve a problem, all the while learning how it really works.
  • Find where that technique or tool also doesn’t work. If I were to hire you, I expect you aren’t going to know everything however the less I have to pay for spending your time on things that you know don’t work the better.
  • You should get really good at not necessarily learning new things from others but focus more on learning from others experience. Its great to learn a new model or method but its much better to learn how others implemented that model or method and what went right or wrong. That is much more valuable to you and your ability to get into the Analytics field.

Analytics Truth #3: How you think matters more than what you think

[bctt tweet=”How you think matters more than what you think -Philip Tetlock @PTetlock”]

Analytics is a space in which we need people who are not glued to a specific outcome but open to possibilities that they didn’t expect. There are simply too many people that want to find nails so they can hit it with a hammer – because frankly that’s all they have. We need people who can truly think outside of the box and think differently, that can think in contradictory terms yet be totally fine with it. Have you ever wondered why physicists make great data scientists? One reason is that they are intimate with data and how to use it but I would offer that they were born or trained in school to think in a manner that forces them to think more openly and not jump to whatever outcome will make everyone comfortable.

  • More and more top analytics companies have changed their hiring processes to focus on extracting the patterns of how a person thinks versus that they can rattle off random equations
  • I can’t emphasize enough spending time on how you think. Find ways to think differently, get rid of taking the first thought that pops into your head. Think of other possibilities. One example of how this plays out is that you can find really great analytics pros and data scientists that are great thinkers are also able to solve most problems in many different ways using different tools or methods.
  • A great method for expanding thinking I know a few people including me use is to find problems in science that haven’t been solved (there are many like this) and try solving them. Spend time thinking through them and finding different ways to even asses the problem. For most Analytics & Data Science people this can be quite a bit of fun!

Analytics Truth #4:  Go broad first then deep

In my conversations with others in the Analytics field I’ve found this is a challenge for most anyone, I can imagine quite clearly how challenging it is for you. So the sub-truth here is that there are very very (think 0.000001% or lower) few people that can go broad and deep into Analytics. There are just too many things to learn and know for someone to become an expert in all things. If you find someone who you might believe just knows everything, the reality is most likely that he/she knows one or two subjects extremely deeply and then can also go very broad in a little of everything or the opposite is true in which this person can knows quite a bit of all subjects yet can’t go very deep into any one of those topics. So for example this person might know marketing analytics like nobody’s business but also understands many other areas of business decently well or maybe he/she can hold their own with any of the experts in the respective subjects but they aren’t the expert.

  • Spend proportionally more time (think 80/20 rule) in learning enough about as many subjects as necessary then once you feel like you understand “enough” then start getting deeper and deeper on specific areas.
  • Apply this to learning tools as well. If you want to do Big Data or Data Science, spend time on learning the landscape of tools and what they do versus finding the first tool and then spending all your time learning that one tool.
  • If you also follow Analytics Truth #2 you will by nature of experience get deeper on what you need to. There are few subject areas that have absolutely nothing in common. Nearly anything you learn (broadly) will have some level of application to another.

Analytics Truth #5: You have to prove yourself (or cream rises to the top)

Because there are so few Master’s and PhD’s coming out of universities and are nowhere near what the demand is there is a huge gap left over. What this does however is put a premium on those who can or have proven themselves. It’s one thing if you just want to work in the back corner of a 50 year old company that never makes more than $1 Million a year and want to be the ‘data’ guy/girl. Totally fine and no one can judge you however, if you want to be successful and work on more problems and bigger problems then you need to prove that you can. I can assure you that companies talk but even more analytics and data science pros talk about those ‘up and coming’ and it would be very advantageous to you to be one of them. Most people want to work with the brightest and smartest.

  • Focus on creating good relationships. Spend time connecting with others and asking questions but do so by being humble and respectful. You can also be the smartest guy/girl in the room but if you are not easy or engaging to work with. Sorry you aren’t going to have many advocates very long.
  • Only say what you know and not what you don’t. Don’t inflate your own ego because you want to be part of the team. Be honest and open about what you can or can’t do. If anyone makes invalid judgements or opinions because you are honest with them then that’s their problem not yours. Don’t worry about those. If you don’t know something then learn it.
  • Find ways to model or follow those that are doing well in the field. There are plenty of great people in this business and truly love helping others get started in Analytics & Data Science. Listen openly and attentively to them when they speak. Find ways to learn what they did. I can’t think of anyone in this field that if you emailed them with a valid and valuable question that wouldn’t answer. Let them be your guide.
Please tell me your thoughts below in the comments! Agree / Disagree? Have any more analytics truths you live by?


About The Author

Joshua Burkhow

Joshua is an experienced analytics professional with focus on areas such as Analytics, Big Data, Business Intelligence, Data Science and Statistics. He has more than 13 years experience in Business Intelligence & Data Warehousing, Analtyics, IT Management, Software Engineering and Supply Chain Performance Management with Fortune 500 companies. He has specializations in building Analytics organizations, Mobile Reporting, Performance Management, and Business Analysis.

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