Microsoft Power BI: Can it be used to analyze crypto data?

Power BI is a reporting tool made by Microsoft. It is geared towards businesses and provides tools like customizable dashboards, interactive visualizations or business intelligence. The interface was designed with simplicity in mind, so it’s easy enough even for new users to create their own reports.

If you do any type of business that handles any type of monetary transaction on a large scale – traditional business, trading stocks, trading cryptocurrencies, or keeping track of your winnings and other information of your winning from playing Grande Vegas online casino – there will be lot of data to go through every month.

The data needs to be stored, and the data needs to be analyzed. In this aspect, trading cryptocurrencies is no different from running a media agency.

As long as your business works on a small scale, then using Microsoft Excel to store and analyze the data will absolutely be enough.

But once your data reaches certain volumes, Excel will not cut it. Larger data sets need to be stored a database, for which you will need a more powerful user interface.

In that case, you may need to look into Power BI.

What is Power BI?

In simple terms, Power BI is “Excel on steroids”.

In more sophisticated terms, Power BI is a collection of software services, apps, and connectors that work together to turn your unrelated sources of data into coherent, visually immersive, and interactive insights.

There are three main parts to Power BI. The first if where the data is obtained from. The second is the report generating of the data. Third is the storage of the final data.

How can you plug data into Power BI?

To start working with a new set of data, the first thing you have to do is to get the data somewhere.

You can either “discover content” or you can “create new content”. Power BI supports all the common time series data sources that you can get from crypto exchanges either in your user account or programmatically via an API.

Supported remote data sources:

File data sources:

Side Note: Parquet (column based data storage) is useful when you only need to work with a small amount of the data. Then you just read in the appropriate column into memory instead of the whole table into memory. This will not be useful is you are working with a dataset that has thousands of rows as the impact on memory would be too big. But if you want to analyze trading data from 50 trades, the column based data storage may make sense. This is actually a “new concept” in data storage, which is why I am making note of it.

Supported Types of Databases:

As you can see, Microsoft prefers their own products but still makes available plenty open source options such as MySQL, MariaDB or SQLite.

In fact, there even more different database data sources available to Power BI. I only listed a few of the most popular. Here is the Microsoft’s Power BI Documentation to get the rest.

Power Platform Data Sources:

Azure Data Sources (Microsoft):

All of the different Azure data sources are supported, but I did not list them all. Azure is owned by Microsoft, so it would make sense that Microsoft Power BI would support all Azure options.

Online Services Data Sources:

The reason that I listed all of them, instead of just the major ones, is to indicate just how vesitile Power BI is. Not even included traditional data flat files and traditional SQL database, Power BI can get data from 49 different online services. And these are not even the “other” data sources that are in the next category.

Summary of all of the places to get data into Power BI

Maybe it is because I was a software engineer, and my first job out of college was exporting data from one database system and importing it into “my company’s” database system (database written by my employer). I look at that list and I am in awe. I wrote the source code from scratch that can now be done in Power BI with just a few clicks of a button.

But even then, I was dealing with one data source. Power BI can handle an infinite number of data sources of different data types, and when you are finished importing into Power BI, what the user sees on the screen is just the data that they want to see. It does not matter that the name of the state came from Wikipedia and the number of births and deaths and population comes from the US Census Reports. It is just data to the end user.

And then you start defining the relationships of that data. When I was doing that way back, I had to write code by hand. Every new dataset was a new subprogram that had to be compiled and tested and documented. But now, with Power BI … it is just a few clicks of the button. The data dictionaries and data mapping and data flow diagrams that I used to have to draw by hand in the past, I just use Power BI templates and arrows (no different than drawing in Visio and Microsoft Word), I connect the data (draw the data relations) in Power BI … click done, and behind the scenes, Power BI does everything that I once had to do “by hand” with custom made code.

Did I mention just how awestruck I am with Power BI and I have not even begun to talk about Power BI’s data analysis, report generation, and saving / exporting the final data, including creating data panels / data dashboards that update automatically as you update your data in Power BI.

I know that the Israeli government used Power BI to display their data on their public website during the COVID-19 pandemic, and I am sure that they were not the only ones.

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