6 Reasons why Business Intelligence is “Hard”.

Tackle these 6 issues to get closer to mastering your BI

  • Are you having a hard time working with data?
  • Is your boss asking you stupid questions all the time?
  • Or are you simply not finding your way in the world of TOO many software solutions that promise you an easy fix?

Well, whatever reason you might have to be here, I’m going to try and help you a bit. Showing you my Top 6 reasons why people find it hard to master Business Intelligence.

#1: Data, data, data…. it’s everywhere!

One of the main reasons why people are having a hard time getting insights or becoming smarter with data is that they simply have too much unstructured data.
In the 21st century, with trends like IoT (internet of things), Big Data, Web Analytics and Data Visualization, data is generated everywhere… in amounts we find hard to comprehend. Where to start? And how do you find data that will make your job easier when you keep swamping yourself?? 😉

#2: I know my Facebook, but why is Tableau such a pain?

There are tons of amazing apps on the internet to help you visualize and analyze data. But using them seems harder than using Facebook or an iPhone with a slick UI.
Nowadays all the newly developed software has easy-to-use interfaces… why are data and analytics apps so different? Creating a nice chart in Excel or some visualization apps like Tableau is a bitch for the average user. Well that’s mainly because most of our commonly used data products are Database driven, that means that talking with them from a user perspective is not as easy as simply liking your friends photo 😉 Learning some basic SQL will help you get the hang of it, but the makers of these tools need to step up too.

#3: KPIs, OKRs, Dashboards, Spreadsheets…

Having a job is great. You boss giving you targets, KPI’s and even OKR’s is good for keeping you focused and challenged!
But one of the major problems with Business Intelligence is focus. What is really important? Where do I find that? Is the most important thing the thing my boss is asking for, or is it just being passed down from his boss? How to figure out what data source you should be using is very very important when learning more about your job, company or product. Rick Klau wrote a nice article on OKRs, check it out!

#4: Where to start?

A lot of my clients ask me where to start when they need help with data or web analytics. Figuring out where to start is a hard thing… You will need to figure out all the things in number 3. What are the companies main goals and objectives? What can you or your team do to help achieve that?
Do you have the answers to this? Great, let’s get started.

  • Pick 2 or 3 simple things based on basic data sources you can easily report or get your hands on. This should get you started and get some motivational 1st results.
  • Take 1 or 2 pain points that need to be solved and find out which data can help to get you the appropriate answers.
  • Reminder: Start small!

#5: Using data requires a certain level of savvy

Honestly… you need to be able to understand some basic stuff about databases. Also, how things are connected with each other. Are there relations between some data streams…? If not (maybe I should have made this point one) stop doing it;)

#6: My Data scientist doesn’t speak my language

One of the hottest new jobs in the market is by far: Data Scientist. Defined by some very impressive skillsets: Very strong analytical/logical thinking, good with algorithms, math guru and highly intelligent. One of the things a lot of marketing or business people actually miss is that they often don’t speak ‘normal’ English. Having a social chat is impossible, but discussing your business model or marketing strategy is something that doesn’t ring a bell with many of them. They need numbers, algorithms some sort of proof.
My advice is to make sure you understand how to work with highly intelligent people like this. They will give you high-value information, generate predictive models for you and will grow your business… Try to learn their language instead. Neal Lathia has some advice from Data Scientist point of view 😉

Thanks for reading!
If you have any other difficulties please reach out or share your BI knowledge with us.

Guy Geeraedts

Work-wise I’m a complete nerd, started playing with computers and nerdy stuff back in the days when I was a little kid. Grew up with tech, IT, software and marketing. Studied a lot to become a marketing guru...

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