Question

Phases of a Power BI Project

Answer 1

Stages of a project in Power BI

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Before starting to use the functions of Power BI, we are going to explain what are the different phases of Power BI or stages, what are the different phases through which a project goes through in Power BI, from the installation of the Power BI Desktop program, to reporting and ways to share these reports with other people..

 

In a learning context in which we are beginning to understand the true potential of Power BI to create visualizations, dashboards and reports, knowing which are the main functions and the most important tools of Power BI, without a doubt, is a crucial part. of learning.

 

It is also of the utmost importance, in this learning context, to understand how these Power BI functions and tools fit within a "phased" project, with different stages. As we will see below, it is a natural and logical process that will provide us with a global vision of the project, and a better understanding of what Power BI is, and how Power BI Desktop can help us when working with data, making professional reports and share them..

 

We will be able to see and learn which stages need to be met when working in Power BI, and why it is important to successfully complete each stage of the project. We will also learn which phases are most important, and what we can and should do at each stage of the project so that the final result of the project is spectacular: a professional, visual, practical and intuitive report that allows information to be displayed from different perspectives, which can be customized. , but, above all, be useful and professional. And that it is valid both for data analysis and for decision making.

 

Stages of a project in Power BI

Next we are going to see through which phases a project carried out in Power BI must go through, regardless of the dimension or size of the project. These are phases that we must definitely comply with when we work with Power BI. In this way, we will better understand the entire process, we will see which are the most important phases, in which phases we should pay more attention. We will learn what the purpose of each phase is, and what tools we must take into account in each of the phases to better meet our objective.

 

 

 

Phase or stages of a Power BI Project:

• Install Power BI Desktop
• Get Power BI License
• Import data into Power BI Desktop
• Data Transformation: Power Query Editor
• Data modeling
• Visualizations in Power BI
• Publish and share reports
• Maintaining and updating reports

 

Install Power BI Desktop

 

 

It is a simple process in which we install the Power BI Desktop tool from the official Microsoft page to be able to start working with the Power BI desktop tool, which is where the important and core part of the project is carried out: Importing the data , modeling and reporting. The perfect complement to Power BI Desktop, as we will see below, is Power BI Service. A Power BI service that, as we will see below, is used for the online publication of the reports, to be able to send the reports, and to be able to work together and collaboratively as a team.

 

Get a Power BI license

 

 

Once Power BI Desktop is installed, we can obtain a Power BI license to be able to publish the reports we make in Power BI Desktop and share them with others in Power BI Service. The use of a Power BI license is not necessary to be able to use Power BI Desktop, as we will explain in the Power BI license types. However, it is advisable to have a Power BI license to be able to take advantage of the options and facilities when it comes to sharing reports, and to be able to work collaboratively online. There are different types of Power BI Service licenses, even a more basic version is offered that is free, and that, although it has some limitations (in the functions of sharing and working online collaboratively), is perfect to start working in Power BI.

 

Data import or Direct Query

 

 

Once Power BI Desktop is installed, and a license for the use of Power BI Service has been obtained or not (we remind you that the license is not necessary to be able to work in Power BI Desktop) we are already prepared at the software level to be able to start our project in Power BI, for which we will need the data that we are going to transform, model and on which the reports are going to be built..

 

The next step would therefore be to load data into Power BI Desktop (called data import in the Power BI ecosystem) or external connection to the Power BI data source. There are two ways to process data in Power BI, import (also known as import mode) or connection to external sources or servers (known as Direct Query mode) where the data is stored. As we will see in the differences between Power BI import and Direct Query, these two ways of working have their advantages and disadvantages. The import mode is generally the most used for two fundamental reasons: It has all the functions and tools of Power BI available for use, and the way of working in the import mode is much more dynamic and fast, having the information hosted, view changes and other operations are executed immediately. In most cases, we also already have the information stored on our PC or in a network folder, and we generally use Microsoft applications such as Excel or SQL Server, with which Power BI has a level of connection and full understanding.

 

Data Transformation: Power Query Editor

 

 

In the data import process, we come across a new concept in Power BI called “data transformation”. This concept refers to the organization, cleaning and purification of data. In this phase we carry out an organization process in which we are providing our data with a structure that will be very important, since we are beginning to shape the imported data, with a logical structure, with a correct format, cleaning the imported data if necessary removing errors, duplicates, blank rows, etc. We make sure that all columns have a header, that there are no blank rows, or cells with errors.

 

In this important part of the process, we can carry out some operations that are vital for the future of the project.

 

All these actions, which as we have mentioned are carried out to structure the data, purify and clean it, are carried out with the Power Query editor, and are within what is called data transformation. We can access the data transformation in the import process, but we can also access it at any time from the Power BI Desktop toolbar, in "Data Transformation", one of the start options. The data transformation process is, as we have mentioned, a process that is carried out with the Power Query editor: the Power BI tool that opens when you click on transform data.

 

 

In this part of the process, there is also one of the most interesting functions, due to the demand of those who work with data, due to its usefulness and the speed and effectiveness with which it is carried out. We are talking about the tools present in the Power Query editor to be able to cross information from two or more tables. Joining two tables in Power BI is possible thanks to the "combine queries" and "append queries" functions; Two functions that respond to information fusion needs when we find disaggregated data found in different files, or on different servers. Through the combination of queries we can cross information quickly and effectively using a column that serves as a unique identifier. With the append query tool,

 

These tools (Merge and Append) are very useful and necessary when the information is separated. In order to make accurate reports that reflect truthful information, we need to build a single database where all the necessary information is found to be able to make the reports. A single data table where all the KPIS that we are going to report are located, a single table where we have all the complete information, and which, as we have said, has a correct structure, does not present errors, or empty cells.
Although you can perform operations within the Power Query editor at this stage of data transformation, it is not recommended. We will leave these tasks (perform calculations and functions) for the next phase of the project: data modeling, data model or also known as modeling.

 

Data modeling phase

 

 

After carrying out the transformation of the data, once we have reviewed the data that we want to import, structured the information, reviewed the errors, eliminated the duplicates and errors that we can find, as well as we carry out other tasks aimed at purifying and cleaning the data. , we apply the changes made and move on to the next phase of the project, called the data model. A data model is a set of data that is organized in different tables related to each other.

 

Data modeling is one of the most important phases, the most important along with data transformation. The reason is none other than to establish, design, and create and organize data sets that will be used later (once the model is created) to be able to create the visualizations, reports or Dashboard.

 

In this phase of the project, apart from being able to relate the different data tables, we can create new columns calculated from the information we already have in order to later create a more complete report. For example, we can calculate ratios that are KPIs or important indicators. As we will see later, measurements can also be created to perform customized and more complex calculations with Da.

 

What is Dax and measures in Power BI

Dax is the formula language that Power BI uses to create measures. Dax is also used to create what in pivot tables we call calculated fields, which are columns to perform calculations such as a ratio, which is calculated based on data from a table already created. As an example, a measure would be to create a multiplication, an average, a subtraction, or a maximum with the values ​​of a table. Thanks to Dax, as we will see later, much more complex calculations can be carried out than taking an average or a sum, with Dax we can carry out more advanced calculations such as the creation of measures with conditional logic, for example, or time calculations.

 

We can also establish different categories or hierarchy in the data and we can also add metadata.
The model phase is as we said key to be able to establish a valid model that helps us to create professional and visual reports. What if we remember is one of the standard values ​​of Power BI. Therefore, once the model is created, we would be ready to tackle the next phase of the project: visualization or reporting phase.

 

Visualizations in Power BI

 

 

Visualizations in Power BI is a part of the project that is directly related to the visualization module in Power BI, and with the tools available in Power BI Desktop to be able to create professional reports, Dashboard with information represented in tables and graphs in an intuitive way. and visual. The tasks that we commonly do in Excel, creating charts and tables with a set of data on a sheet, are called visualizations in Power BI. It has a specific section or module from which we can begin to "paint" the data.
The reporting phase is also a very important phase of the project in Power BI because it is where we are shaping the product, it is the result of the work carried out previously, where we have to have the skill to create interactive visualizations that help in the interpretation, in the analysis of the data, and in the decisions that must be addressed.

 

Within the visualization module, as we will see later, we have many tools and visualization options to create a professional, visual and intuitive Dashboard with relevant data tables, graphs that show the trend of the relevant KPIs, flowcharts, cards, geographic maps, etc. Thanks to this set of tools, Power BI allows us not only to present the data in a professional manner, but also facilitates the interpretation of the data, helps to identify trends, locate behavior patterns.

 

As we have said, one of the standard values ​​of Power BI as a Business Intelligence tool, is in the capacity of data processing, calculation, and in all the tools that, both in data transformation and in modeling, allow us to They allow obtaining valid data sets to work with, which are connected, in order to create more complex reports taking into account the globality of the information. But as an analysis tool, Power BI is a tool that also excels in design tools and configurations for reporting.

 

One of the most notable benefits of Power BI, as we have already seen, you know, or you can intuit, is the ability to generate very visual interactive reports, which look very professional, and provide a degree of automation in all processes. which is key to seeking our productivity, and the productivity of our team.

 

As we will see later, it allows Power BI reports to be interactive and customizable so that people who use our reports can apply filters and therefore see the data from different perspectives, all in real time. Power BI also allows you to add comments to the reports, something very useful as we will see to be able to work collaboratively.

 

As we already saw in the course of pivot tables, in Power BI it is possible to perform data segmentation and connect tables and graphs to obtain a fine consistency in the reports, with respect to the data that is displayed.
Once the reports were finished, we would move on to the last phase of the project: publishing and sharing the reports in Power BI.

 

Publish and share reports

 

 

Publish and share reports in Power BI: In order to share the reports made in Power BI Desktop, we are going to need a Power BI license, which, as we already explained in the Power BI license types, we can choose between the free version, Pro and Premium. Depending on the sharing needs, and the volume of your projects, you will need one license or another. From Power BI Free, the free version of Power BI you can create a report with a link that you can share. However, if the data to be shared is confidential, we should opt for one of the payment options. The paid versions also allow us to work collaboratively with other users, to be able to create groups to share ad hoc information, that is, to establish different levels of information to, for example, be able to report to management,

 

Update and maintenance of reports

 

 

Once all the previous steps have been carried out, in a last phase we must carry out the maintenance and update tasks of the reports made, especially when these reports are used to report periodically. For example, if the reports made in Power BI are used to report the sales made by a company every week, each week we will need to update the reports with the updated data for each week. Report updates is a very common task, because even in the case of having to report less frequently (for example, annual reports) having a template and a design already done will speed up the reporting; we will only have to worry that the reports are updated up to the corresponding date, and of course that the reported data is correct. As we will see, the automation of tools such as Power BI when carrying out projects goes one step further and establishes very simple mechanisms so that once the reports are completed, this maintenance and updating task is a very quick and simple process.

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