Jones - Power BI: 3 in 1- Comprehensive Guide of Tips and Tricks to Learn the Functions of Power BI+ Simple and Effective Strategies+ Advanced Guide to Learn the Advanced Realms of Power BI

Business Intelligence Software (BI)

Business intelligence software is capable of turning large volumes of data into analytical and summary dashboards. They are configurable and capable of automatically executing the routine of data collection, treatment1, analysis, and visualization. The term BI began to be used for technology in mid-1958. From the initial letters of business intelligence, it was tied to software capabilities of transforming the way much information was consumed in Hans Peter Luhn's article " A Business Intelligence System ." The computer scientist, who was currently working for IBM, described BI software as automatic systems designed to propagate information to various sectors of the economy. His research, among the developments of more than 80 patents, was initially applied in IBM analysis software.

Nowadays, there are many business intelligence software in the world that provides the basis for the functionalities that software of this category should offer, such as data analysis through calculations using different languages, connection to external sources in various ways and data visualization with specific graphics and with its own design and configuration. Given all of its similarities and differences, one of the most relevant in Power BI is the learning curve.

Perhaps because of the strategy of making some of its resources available in Excel before its release (Power Pivot and Power Query), but certainly not only because of that but because of the very way it was logically architected, the learning of languages and the process of building projects in Power BI is considered by us one of the fastest and most consistent, enabling results at a higher speed than many software in the same category.

Research that supports and shows some of the reasons why we, as business intelligence experts, chose Power BI as the leading BI software is published by Gartner, a leading global company focused on research and consulting in several areas of information technology. Every year an extensive report and graph summarizing it, called the "Magic Quadrant of Analytics and Business Intelligence Platforms," are published with analysis of BI software, being analyzed 15 critical aspects involving infrastructure, data management, analysis and content creation, discovery and sharing, ease of use and return on investment. Power BI is identified as "Microsoft" and is in the top direct quadrant, i.e., the market leaders today.

After downloading, open Power BI Desktop and you will observe each numerical legend commented below.

1. This is the Power BI ribbon containing the Home Page, Display, Modeling, and Help. It is through this interface that the database connections, the Query Editor (Power Query), the data modeling options, the panel layout and others are accessed.
2. The three buttons located on the left vertical are called the Report, which is the blank panel displayed in the previous image data, which displays the data imported into the Query Editor. And Relationships, which show the tables and allows the relationship of their key fields.
3. Set of Power BI views. Initially, only the default views will be shown, but hundreds of others can be added by the Marketplace, and can also be created with the R language.

Treatment Of Data In Power Query

Power Query Editor is a free add-on created by Microsoft in 2013 for Excel 2010 and 2013 and later also included in Power BI. It is the intuitive tool that allows you to transform, maintain, manipulate, consolidate, merge, enrich, and do much more with your data.

It acts like the ETL (Extract, Transform and Load) tool, extracting data from nearly any source, transforming it and then loading it elsewhere - in this case, Power BI or Excel. The Power Query Editor interface is separate from Power BI, and its window opens when you click Edit Queries. The function language M is its base, coming from the term data mashup, i.e., obtaining and combining data.

There are over 600 functions in M language that, when combined, provide comprehensive variation for data collection, processing, and joining. Its main concept is in the automation of this whole process, being necessary to connect only once with the data source and treat it so that the next updates follow the same pattern. Among the categories of functions available, we have: