So far I’ve mostly written about databases, and adding data to the database. Once you’ve done that, then what? When your data is in one place, it’s time to let some magic do its work. Merge it together, create synergy and make it even more valuable.
What is merging: Merging datasets is the process of bringing datasets together by a common attribute of column.
A few examples:
Merging facebook ads data together with google analytics data so you are able to see expenses, impressions, ctr or conversions of different online marketing channels in one chart or table so you are able to compare them. It could help you answer questions like: Is it worth spending your money on Google Ads, or are the most sales being done via social or organic?
It is just one example of many, I’m just trying to point out why it can be important to merge data.
Another example is connecting profits that a business makes with expenses, over time. How much do you spend on recruitment? What part of the business do you make the most money? How much does your business spend on employees, sickness, recruitment, HR compared to how much money is spent on advertisement? Does it make sense, or should it be changed? Plenty of questions, probably random data, different systems, different sheets, but bringing this data together, merging, could be so, so important to improve your business, make decisions, let it grow.
As you might have guessed, in order to bring this data together, data sets need to have something in common like date, campaign names, scores, countries, totally depending on what data it is. This is crucial. As a data analytics consultant you can change a lot, but if there is nothing in common, you can’t merge the data into the same file. All of the examples above are interesting to consider before running tests and collecting data. Often it’s more important that you think about all of the above before you even start analyzing. Again, if you can’t merge the data, you’re unable to analyse it in one file and transform it into valuable insights by vizualisation.
Do you need to merge everything? No, definitely not. But merging some specific data will create a synergy and gives you insights that otherwise you wouldn’t have had.
When to merge the data
When you have found the common joiner, and you have merged it together correctly in a file, WIN!! Important as well to mention that you want to merge this together in a separate table or view in MySQL or BigQuery, and not try to merge it in data studio, power BI or tableau. Reason for this is that if you let data studio do it, you can’t see exactly what it going on and therefore you’re kinda left in the dark. You can’t check how it is merging, what exactly is merging and whether that’s right or wrong. It also does not give you the opportunity to tweak or adjust the merged data. The lack of control is the main reason for me not to use it. Besides that, almost every time I tried using it, it ended up in wrong data, not being able to change it, and it made my data useless. I had to go back to bigQuery or MySQL to adjust it, which is absolutely fine, but it felt like a waste of time trying to figure it out in data studio. So that’s a no for me.
Show data in data studio
One of the programs you can push your data to is data studio. It’s free, and gives you the opportunity to provide understandable and meaningful insights. This is where your data turns into (useful) information. You visualize the data. Data vizualisation is a whole different topic that is a separate item on my website. You can visit that page HERE.
Apart from data studio, there’s plenty of more data visualization tools available (paid & free). Most of it kinda works the same so if you use something else, that’s obviously fine too.
As usual I’m always open for feedback, or just a chat. So feel free to contact me.