Getting started with data analytics can be easier than you think
Over the last few years I've come across many organisations and people who wish they could be doing more with their data or at least take their very first steps into the world of data analytics. These are often unfulfilled wishes because, for the most part, many do not know how to get started. Often times these places and people will think that to get started you need to bring in consultants which can be expensive or get your people onto expensive training courses. Both of these can be viable options if you have the money but for many smaller and medium sized operations it can be a risky choice. Luckily, I'm here to introduce you to some inexpensive ways to get started, especially if you have the time and resources to experiment.
My idea for this is that by sharing this information, you can take the first steps into unlocking the untapped potential of your organisation and yourself. Also, it serves as a good sneak peak into the inner workings of the analytics tools that are often used in the broader business intelligence marketplace. By looking into things like this you get a leg up on knowledge prior to starting any training course or engaging with consultants and perhaps you may even be able to learn how to use a tool to build your own dashboards and reports without the need to pay for any external help at all. However, the caveat here is that I am not advocating that we ignore external help at all. Rather, you can vastly accelerate your experience if you start at step 50 when you bring in outsiders than starting from scratch.
Many of the tools that I use or that are available in the marketplace are free to download for personal use and many don’t have time restricted trials. Whether it’s for marketing or promotion purposes it certainly works and by trying things out for yourself, you can help save on the costly process of being trained on how to use a tool but then forgetting how to do everything you were taught because you don’t get to use it day to day. Try before you buy is a bit of a catch cry in the business intelligence community and you do yourself many favours by taking advantage of all the free stuff you can get.
So why should you look at this? Well, its not necessarily just about making reports look good. Sometimes, simply joining different datasets together can give you a lot of insights. It can show you that your data might have duplicate names or even mismatched ones (e.g. a Country field in a table of data that has many listings for the same country like USA, United States, U.S.A.) or it might help you see that the users who spend the most time on your site are not necessarily the highest paying. Just these 2 examples can lead to so much innovation in some organisations that it’s almost wrong to not try to do it.
So if you do get started, how would you go about doing it. Well, it depends on the style of learner you are. Those who are more hands on, like myself, will simply find the tool, download it and start playing even before reading the instructions. Obviously, you’ll run into a few dead ends but you learn while you do it. Others might prefer the guided instructions that many of these software tools provide for free (yes FREE) on their websites or via YouTube. To that point, here are my quick start methods if you were going to get started with some of the better known tools out there.
Qlik Sense / Qlikview
Definitely one of my trusty go-to’s in the world of data wrangling. Like a good wrench or hammer, Qlikview, and more recently, Qlik Sense have been at the forefront of my problem solving steps and continue to be used by my team and I to this day. What’s great is that they have developed very cool and easy (via drag and drop) ways to join datasets together. Once you get to know how to use Qlikview or Qlik Sense it becomes so easy to bring different datasets together. Qlikview used to be the pre-eminent tool for those without a fancy database with which to do data prep (i.e. just join all of those different excel files and data from the web easily) and could do handle a lot of data with speed. I know that Qlik Sense had some catching up to do with the type of loading tools it gave clients but it’s there now and it has hands down, the better visualisations than its predecessor.
To get started with Qlikview you can get it here: https://www.qlik.com/us/try-or-buy/download-qlikview
Qlik Sense can be downloaded here: https://www.qlik.com/us/try-or-buy/download-qlik-sense
Some getting started videos on Qlikview:
And for Qlik Sense:
Microsoft Power BI
The newcomer to the group but certainly the most intriguing. Whilst this blog is not about costs, they are certainly the cheapest to get started with at the next level above free (Pro users are charged US$10/month) You’ll get a lot of value out of that and better yet, for most Microsoft Office 365 type firms, the software comes already available as part of your suite of products. The most intriguing prospect here is the wide variety of integrations you can have with your other Microsoft tools. Imagine your users filling out a survey form you created using Power Apps where the answers guide their experience in Power BI. You can then use Flow and Dynamics to automate the campaign/marketing messaging that goes to those users. Even integrate your Visio diagrams so they’re interactive in Power BI. The connection possibilities are amazing but to get there you need to get started loading data!
Download Microsoft Power BI here: https://powerbi.microsoft.com/en-us/
Then check out these great intro videos on how to get started:
Another great tool which has had limitations over the years with its data preparation but the way it can serve up visuals either in the cloud or via internal reports is second to none. It’s ease of use and ever growing list of advocates have helped it become a mainstay of the leadership group in the business intelligence community. They’ve gone leaps and bounds to improve how they load data and allow you to do much of that within the tool as opposed to the ominous task (for some) of having to prepare your data in SQL server or other databases first (a good reason why many chose Qlik tools over it).
To get started you’ll want to download a version of Tableau which you can do here: https://www.tableau.com/products/desktop
Then check out this getting started video:
Yes, even the common excel which has been the bane of many an analysts existence can be quite powerful. With the advent of further Microsoft Office upgrades, they’ve made the ability to create simple dashboards quite easy. These even incorporate filters/slicers so that you can give the user an almost integrated dashboard type experience. The downside here is that it’s going to be limited by the amount of data you have in your model and I’m sure some of us have had the dreaded experience of opening up large (think > 100 mb ) Excel file and waited minutes for it to render.
This video shows how you can create a very cool looking and interactive report just using Excel:
What’s next you ask? That’s where it becomes interesting because it depends on your goals. If you’re a university student looking for a way to make your report stand out from the crowd then you’re going to want to make your visualisations stand out from the crowd. If you’re an analyst looking to improve a mundane work process then you’re after speed and potentially automation and certain tools do that better than others.
Another myth that should be quashed is the one where people believe you need to have 1 tool to do it all. That’s just not true. If you could then that’s very lucky but some tools are much better at doing some tasks like joining/loading data than others. It may also be the case that you are more experienced with data loading/joining/aggregating with certain tools but then use others to do your visuals.
Each of these products continue to improve their offerings so you might eventually find something that does everything for you. But until you get there, the best solution is going to be the one where you use the right tools to your advantage. Time to get on board don’t you think? Whilst you certainly won’t necessarily be a data scientist by the time you’ve looked at or tried out the above, at least you’re not going to be so daunted the next time you start having a conversation and the data buzzwords start coming in.
See you next time.