Posted in Data
The robots are coming for us.
I’ve written before about the gnawing anxiety many of us feel about the threat of technological change engulfing us all. This is more applicable to those of us working in technology-centric jobs But there are few areas these days that aren’t under threat from the terror of being automated out of existence.
The technological change doesn’t have to be as high tech and innovative as self-driving cars or robotic assembly lines. In analytics and business intelligence it could be as straightforward as a new BI platform replacing the manual production of reports.
It makes complete sense to spend the time upfront ensuring your data warehouse and ETL processes are fit for purpose. Build out the reporting infrastructure and the power of the platform removes all of that old-fashioned human drudge work.
Good news for users. Great for the business. But not so good if you were one of the staff cobbling together the reports. Where do you go next then when you find yourself being automated out of your BI job?
When the comfort blanket isn’t so comforting any more.
Data scientists are supposed to be the new rock stars of the analytics world. But how good are your future prospects if you don’t have those few years with a Data Scientist job title to pad out your CV? What if your role wasn’t even titled as a Data Analyst?
What if you got rather cosy in your small remit and actually just copied and pasted data from reports generated from another data delivery team? Maybe your saleable skill-set really only covers Excel? Is there a place for you in this bright, shiny new analytics world?
Of course there is. But it’s high time you gave yourself a shake. You need to start looking at what you really have to offer AND where you can start to level up your data skills.
We’re going to look at two specific areas which will give any MI analyst the best opportunity of carving out a new seat at the table for themselves.
TOP Tips For Those Who Want To Survive
#1: Learn SQL.
Forget Python, forget R, forget Machine Learning or Hadoop or Hive or Spark or any of the other sexy shiny new technologies you’ll read about on r/DataScience. At this point, they are as useful to you as the proverbial ashtray on a motorbike. Ignore them.
What you can not afford to ignore are the basic fundamentals of SQL. Learn your SELECT, UPDATE, INSERT and DELETE statements. It’s not glamorous. It’s not particularly rock n’ roll.
Reeling off a few SQL statements is unlikely to get you any positive attention from your preferred sexual partners at any time of the day or night. Maybe that’s just me though.
If you are coming from a position as a 100% Excel Jockey, it will move you up a level in terms of expertise and career desirability.
Don’t skip this one – You can NOT afford to miss this step.
I’ve spoken to business managers in many industries. The consensus is that if a consulting company sent them over a data analyst who didn’t know SQL, they would never use that company again. It’s that important.
My skin crawls at the memory of some truly horrible SQL statements I’ve been asked to QA. But I’d rather see someone giving it a go and learning from their mistakes than ignoring this gaping hole in their analytics arsenal.
SQL – Say it (and I don’t care if you pronounce it S Q L or Sequel). Know it. Love it. It’s your new best friend.
#2: Business Knowledge and the Communication Thereof.
Are you one of that pot of people who haved worked in a reporting job for years and still have absolutely no notion of what the numbers actually mean in context? I hope not. After a couple of years experience, you should have built up a wealth of business domain knowledge. If not then maybe this whole data world isn’t really for you. You might be safer giving Uber a shout for a couple of years before the self-driving cars come in.
If you have then you need to start letting other people know just how much you know. Even more so, let them know how expensive the loss of that knowledge would be if you were shown the door. A varied, long running career in many different areas of one business doesn’t necessarily send up too many red flags for me. We know organisations change over time. Moving from area to area can help give you a more rounded view of how the whole business inter-operates.
Getting pigeon-holed is good to go deep on a subject but I think it’s detrimental over too long a period. If you’ve been bounced from role to role because of HR issues however that’s another matter entirely. All of the domain knowledge in the world shouldn’t save you. Another set of stories for another day perhaps.
Bringing it home
Always remember that you don’t have to be the fastest mover in the office. Just a little faster than the slowest member of the herd. If you keep levelling up your skills incrementally at each crunch point, it won’t be you getting picked off by the cost saving lions.
Go with the fundamentals. Get your basic SQL sorted. Let people know just how much you know about the business. Knowledge is power after all and we all need a little power behind us when the wolves of progress start closing in.