In our previous article , we highlighted that organizational structures and corporate cultures play a major role in data analysis, in addition to technology. Now it's time to return to good old IT.
A very important step in becoming data-driven is introducing business analytics into the organization, which cannot be achieved without BI tools. However, to successfully overcome this obstacle, we need to choose the right tool.
Currently, the two most popular tools on the market are Tableau and PowerBI. In order to choose between them, we need to know the scope of future users. It doesn't matter whether an analytics team will lead analytics projects in the organization or we want to put an analytics tool in the hands of "ordinary" business users.
In terms of the end result, we can expect the same from both tools: interactive dashboards that can answer business questions. All of this can be accessed by users on a regularly updated, shared interface according to their set permissions. This way, we can provide informative, easy-to-understand, customizable reports and analyses to those who request them.
The tools are very similar in their capabilities. They have a data preparation interface, from which we can go directly to the analysis interface. We can use them to perform quick data discovery and then return to the data cleansing interface if we need to make any further changes. We can create basic analyses using the drag&drop method, create our own calculated fields, and use the built-in analytical capabilities.
Both tools can be connected to almost any data source and provide the ability to use the data found there, all without in-depth programming knowledge.
It is precisely because of these similarities that they often do not even consider comparing them further before deciding on implementation. However, it is worth considering another aspect to truly implement the right analytical capabilities to create business value, and not just provide another tool that everyone tries to circumvent with loopholes or use according to their own needs.
This aspect is what basic technical background the future users have. In order to exploit all the possibilities inherent in Power BI (and with its help we can really go far in the field of business analytics), it is worth dealing with the functions a little more deeply, perhaps getting acquainted with the DAX or M language. Let's not think about things more complicated than Excel macros here, but as we have experienced many times, the majority of business users are reluctant to go this far. Not because they are not capable of it, but because they simply do not feel it is part of their job to extract information from data by acquiring technical knowledge. However, if they do not have the time or affinity for this, and data analysis is not closely part of their job, they need to be provided with a tool that allows them to rely on the data without it. In such cases, it is worth choosing Tableau as an analysis tool. The learning curve for acquiring the knowledge necessary to use it is steep – so you can start using the tool quickly, with basic knowledge – and the analytical capabilities are easy for anyone to exploit.
User-friendly data analysis options and tools that anyone can easily learn are here. Being a data-driven company is not only worthwhile, but necessary. The only question is when, what, and how to implement them in your own organization so that your important business decisions are based on accurate data, not luck.