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Power BI – an Asset for Data Analysts

  • Rafat
  • March 20, 2022

This article is going to focus entirely on data analysts using power bi to help them with their daily tasks and responsibilities.

If you have read my previous articles on Power BI, by now you already know what it is including some of its basic applications. One thing I should highlight is that when I say “Power BI,” the words “Data” and “Visualization” should immediately come to mind. Why is this so? Because Power BI would be (and is) meaningless without data. No power bi process can be finished unless and until it has data loaded in it. Data is basically sets of structured and unstructured information.

The first option you get when you open Power BI is literally “Add data to your report.”

learn power bi

Once you’ve loaded data into Power BI, you can easily visualize it. Power BI is a really strong tool for visualization of data. Visualization of data makes it easy for others to understand data in the form of a story.

However, did you know that data analysts also learn power bi since it helps them with their work? Why should a data analyst learn Power BI and why is an asset to them? We will understand that in this article.

Let us first revise who a data analyst is and also understand a data analyst’s basic duties and responsibilities.

Who Exactly Is a Data Analyst?

A data analyst is someone who works with sets of information. In order to solve a problem, he or she gathers, cleans, interprets, analyzes, and visualizes sets of data. He or she serves as a gatekeeper for an enterprise’s data, ensuring that all stakeholders are aware of it and can leverage it to make smart business choices.

Daily Tasks of a Data Analyst

According to an Udemy course (Microsoft Power BI: DA-100 Data Analytics using Power BI), the sequence in which a data analyst supposedly works is:

  • Prepare,
  • Model,
  • Visualize,
  • Analyze,
  • and, Manage.

Let us understand them individually.

Prepare

The first thing that a data analyst needs to do is to prepare data.

According to SearchBusinessAnalytics, “Data preparation is the process of gathering, combining, structuring and organizing data so it can be used in business intelligence (BI), analytics and data visualization applications.”

The reason why data needs to be ‘prepared’ is to identify and separate meaningful and important sets of information from a huge chunk of information. It is basically converting raw and unstructured data into meaningful and structured data that can be easily understood. It involves verifying the preciseness of the data and producing reports on it. Not only that, but it also includes modifying the data such as locating any missing data.

Model

After preparing the data, move on to the next step. A data analyst needs to model or structure it in some way. It simply means arranging data items and establishing a framework for how they relate to one another. It is the technique of using text and symbols to represent the data and how it flows in a condensed layout of a software system and the data element it includes. A data analyst takes existing information and improves it by defining indicators and introducing custom adjustments to enrich the data model.

Visualize

Data is ready to be visualized once it has been prepared and modelled. If you’re asking why there’s a need to visualize information, the answer is simple: to effectively convey that data. Information in the form of graphs, charts, and so on improves understanding of that specific information. As a result, a data analyst basically generates multiple reports using the existing data after preparing and modelling it. Each report would include a variety of graphs and charts, each containing valuable information.

Analyze

You’re probably assuming that once the data has been transformed into charts and graphs, the job is done. However, it is not for a data analyst. This is when their primary role comes into play. A data analyst looks through all of the reports, thoroughly assessing and interpreting the information. He or she searches for patterns and trends, looks for outliers, predicts outcomes, and then communicates them in an understandable manner. Here they can learn power bi to analyze information in an effective manner.

Manage

A data analyst is responsible for managing all reports, dashboards, and other tools. They must manage all information and its distribution, as well as maintain its confidentiality.

Power BI’s tools

The following are some Power BI tools that can assist a data analyst in doing the prior tasks using the desktop application:

  • Preparing Data: If you want to organize data, Power Bi also allows you to manually paste data into a blank table in the desktop application itself.
  • Modelling: To establish a data model in Power BI, just add all data sources to the Power BI new report option. (You can do this by visiting the “Get Data” option, which I mentioned previously.) You can do various things such as add new columns, tables, new parameters. On the extreme left (circled section) you will come across 3 options which are report, data, and model. You can easily model your data using Power BI. This is one of the only data visualization tools which also enables data modelling.
Modelling
  • Visualizing: Visualization of data has become really easy using Power BI. It enables the creation of enhanced data representations and designs. Power BI features an entire area devoted to “Visualizations,” which includes a variety of charts and graphs, python and r script visuals, and much more. Info can be imported from any data source and converted into a chart or graph by anybody. Power BI makes it extremely simple for data analysts to create reports and dashboards.
  • Analyzing: In Power BI, analyzing any graph or chart is quite simple. For example, if I wanted to see information for a certain month out of 12, say July, I can simply left-click July, and all of the charts in the dashboard will display only the charts for July. (Hovering over the charts reveals more information.)
  • Managing: One can easily manage Power BI reports, dashboards, workspaces, and much more.

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