Clean, Shape and Calculate Data in Microsoft Power BI Desktop

Those preparing for the Microsoft Power BI certification have to bear in mind the fact that the certification is the official validation of the skills that Power BI imparts. This means that if you take up this certification exam after having worked at some depth with the concepts that go into it, such as data visualization, Data Analytics, data analysis expressions (DAX), business intelligence, and have a little familiarity with the way Microsoft products are created and work, it is a lot easier.

Viewed the other way, anyone who attempts this certification exam without prior exposure to any of these elements that go into the tool will, naturally, find it difficult to handle.

For those who want to prepare for Power BI certification, Microsoft offers a very welcome training course.

It is the Power BI Developer in a Day course. It is a video-based course, whose objective is to help develop the technical knowledge needed to embed Power BI content. You can learn the skills required for becoming an app developer.

To answer this question, the Power BI Developer in a Day course has 2 hours, 20 minutes of viewable content. Offered completely free of any cost, it is made available on demand.

Nothing to worry. Those who miss a Power BI online training course can view it on their LMS. They can attend any subsequent live batch to catch up with what they have missed.

Microsoft has a very helpful Power BI Support page. This should answer your queries relating to Power BI.

Most online learning platforms make their Power BI course content available immediately after the learner signs up. However, check up with your provider if there is a specific timeframe for this.

In most cases, yes. A learning platform like SimplivLearning offers training courses that are both live and available as a recorded version for an unlimited duration, and at a very reasonable price. 

The major advantage of taking up online training courses is that they:

-      Are guided and focused towards teaching all aspects of the Power BI tool

-      Are taught by experts who are aware of all the industry trends and updates about this technology

-      Are flexible to suit your work schedule and convenience

-      Add amazing value to your CV

-      Make you more employable.

Microsoft does not specify any particular academic qualification for those who want to take up the Power BI certification exam. However, it is aimed at professionals who work in data and business intelligence. It is these skills that the Power BI certification sharpens and fine tunes.

The PL-300: Analyzing and Visualizing Data with Microsoft Power BI exam is priced at USD 165.

The MS Power BI certification is certainly worth it since it comes with the following benefits:

-      It tells your employer that you have sharp insights into the business’ most critical resource: data

-      You assure your employer that you have the skills to prepare, model, analyze, and visualize data, and to deploy and maintain assets

-      The certificate is valid all over the world, which means that a Microsoft Power BI-certified professional is sought after by companies of various sizes from around the globe

-      A candidate with a Power BI certificate is considered a prime employee

-      A Power BI certificate is an assurance of a higher pay

-      The Microsoft-issued Power BI certificate has an unlimited shelf life, that is, it has no expiry date.

Microsoft’s Exam PL-300: Microsoft Power BI Data Analyst has a fixed price of USD 165, and this price is based on the country or region in which the exam is proctored. What this means is that the equivalent of this amount is charged in the local currency.

Neither Microsoft, nor any learning platform which certifies you for your Power BI skills gives a written assurance of a placement upon completion of the Power BI course.

However, the skills the certification impart are normally enough to drastically increase the chances of an employer offering you a position.

That is your choice. Most learning platforms, such as SimplivLearning usually offer virtual, live classroom training. By this delivery method, you attend live, online, instructor-led training that is fixed for a suitable day or days of the week.

A few platforms also offer recorded versions of the same learning, which can be accessed at any time of your convenience

Or, you could also choose a fully in-person certification training, which some platforms offer.

Finally, the delivery method that you choose for your Microsoft Power BI training course is entirely your decision.

A Power BI certification increases your job prospects by adding value to your resume.

The Microsoft Power BI certification exam has between 40 and 60 questions, which have to be answered in 100 minutes.

The questions are of varied formats, such as case studies, drag and drop, multiple choice, list builds, true/false, and so on.

Well, there is no unanimous, single answer to this question. There are many ways of shaping data for Power BI.

Loading all tables from the data source is a popular method of shaping data. However, this is only a thumb rule.

These are some of the ways by which data can be shaped for Power BI:

-      Remove columns and rows from a table

-      Add an index column to a table

-      Implement a sort order

-      Group rows

-      Pivot columns

-      Create custom columns.

-      You can select certain columns using Remove Columns option, and remove data from the Power BI local dataset. This method doesn’t change the original data source.

-      Use the Remove Other Columns option.

The ways of shaping and combining data in Power BI are explained very neatly in this Microsoft help page.

In simple terms, you can do these steps:

-      As a first step, import the data from a web source

-      Go to the Navigator dialog, select Table 1 from there, and then choose Transform Data

-      This opens the Power Query Editor window

-      Next, change the table name from the default Table 1 to Retirement Data, then press Enter.

a.     When shaping or transforming data in Power BI desktop, the source data remains unchanged

b.    When shaping or transforming data in Power BI desktop, the source data is also shaped and transformed

c.     The order in which you shape data doesn’t matter. All the data comes out the same.

Answer: a and c.

You can change the shape of data by applying any of these methods:

a.     A predefined shape or line style

b.    A different shape fill

c.     A different shape outline

d.    A different shape effect.

More detail on each of these can be had from this explanation in the Microsoft help page.

Cleaning data consists of five steps:   

-      Removing duplicate observations

-      Filtering unwanted outliers

-      Fixing structural errors

-      Fixing missing data

-      Validating the data.

These steps are mentioned in greater detail and clarity on this Tableau page.

Obviously, there is no one single, universally accepted definition of the best way to clean data. Cleaning data is not one step, but a set of processes, all of which work in tandem with and complement each other. It can be done in the following ways:

-      Removing unnecessary values

-      Removing duplicate data

-      Using a clear format

-      Translating language

-      Looking out for missing values

-      Correcting typos

-      Converting data types

-      Removing unwanted outliers.

The simplest definition of data shaping in Power BI is changing the data by carrying out tasks such as these, among others:

-      Renaming columns or tables

-      Changing text to numbers

-      Removing rows

-      Setting the first row as headers.

Microsoft has a pretty detailed explanation of these functions on its Power BI desktop tutorial.

Yes, you can. You can explore this aspect from this wonderfully helpful Microsoft page

Creating a calculated field in Power BI consists of a series of steps:

-      Right click on the desired category/sub category or select the ellipsis next to it in the Fields pane, and choose New column from the menu. The Formula bar appears along the top of the Report canvas, which will enable you to name your column and enter a DAX formula

-      The default name for a new calculated column is Column. New columns will be named Column 2, Column 3, and so on, unless renamed

-      After the equals sign in the desired category/sub category, type r. A dropdown suggestion list shows all of the DAX functions beginning with the letter R. Selecting each function shows a description of its effect. As you type, the suggestion list scales closer to the function you need. Select RELATED, and then press Enter

-      Select the desired category/sub category, press Enter, and then type a closing parenthesis

-      After the closing parenthesis of the first expression, type a space, ampersand (&), double-quote ("), space, dash (-), another space, another double-quote, and another ampersand

-      Enter an opening bracket ([), and then select the desired category/sub category column to finish the formula

-      Complete the formula by pressing Enter or selecting the checkmark in the formula bar. The formula validates, and the desired category column name appears in the sub category table in the Fields pane.

You can learn a lot more about this from this Microsoft tutorial.

Data calculations are done in multiple ways in Power BI. You are offered a plethora of options for calculating your data in Power BI, in many number of combinations.

We would guide you to this really painstakingly detailed Microsoft page, which is an excellent, full-length tutorial on how to calculate data in Power BI. Going through it in detail is the best lesson you can get on how to calculate data in Power BI.

All the steps in data cleaning are important, but the two principal ones, from which others follow, are:

-      Shaping the initial data

-      Combining multiple tables into a single data.

This said, this is a subjective assessment. The best guide that you can find for gaining more knowledge of the two main steps in data mining is this highly helpful Microsoft tutorial.

Data cleaning in Power BI using Extract, Transform, and Load (ETL) can be done in multiple ways. These are just some of the popular ones:

-      Making data entry manually

-      Using cleaning tools, such as OpenRefine (previously known as Google Refine), Trifacta Wrangler, Winpure Clean & Match, TIBCO Clarity, etc.

-      With SQL queries.

Definitely, by using the New table feature in Report View, Data View, or Model View of Power BI Desktop.

To help users with this feature too, Microsoft has created a very helpful help page.

Data cleaning is data correction at its barest, with the intention of maintaining data accuracy, consistency, completeness, reliability, and hygiene. There are innumerable real life examples that one can think of for data cleaning.

Data concerning personal information, complex business data, or government-related information may be taken up for cleaning.