Introduction to Power BI

1. How To Install Power BI?
To get Power BI Desktop, you can use one of the two approaches.

• Install as an app from the Microsoft Store.

• Download directly, as an executable you download and install on your computer.

2. What Is A Data Model?

Data Modeling is one of the features used to connect multiple data sources in the BI tool using a relationship. A relationship defines how data sources are connected and you can create interesting data visualizations on multiple data sources.

With the modeling feature, you can build custom calculations on the existing tables and these columns can be directly presented in Power BI visualizations. This allows businesses to define new metrics and perform custom calculations for those metrics.

In short, a data model is a collection of

• loaded tables of data

• relationships between the loaded tables

• the measures (formulas) written that apply the business rules to the raw data to extract business insights (e.g., sell price minus cost price is profit), including

  • the formulas themselves

  • the formatting applied to the formulas

  • the business names were given to the formulas

Power BI Desktop has several components to transform, model, and visualize data and also generate reports from data. The Query Editor in Power BI is used to transform or edit data files before they are actually loaded into the Power BI.

The Query Editor plays the role of an intermediate data container where you can modify data by selecting rows and columns, splitting rows and columns, pivoting and unpivoting columns, etc. The changes made by the Query Editor in Power BI are not reflected in the actual dataset. Once you have pre-processed the data and have transformed it into the required format, you can load the data into the Power BI environment.

An append operation creates a new query that contains all rows from a first query followed by all rows from a second query. The append operation requires at least two queries. These queries can also be based on different external data sources

The append operation is based on the names of the column headers in both tables, and not their relative column position. The final table has all matching columns from all tables appended. If the tables don’t have matching columns, null values are added to the unmatched column. The tables will be appended in the order in which they're selected, starting with the Primary table.

You can perform two types of append operations. With an inline append, you append data to your existing query until you reach a final result. The result is a new step at the end of the current query. With an intermediate append, you create a new query for each append operation.

In Power Query, you can add new columns by providing one or more sample values to help create it. You can do this from a current selection or by providing input based on selected columns. This is useful when you know the data you want in your new column, but you're not sure which transformations to use.

A fact table is a table full of Facts!, you know that fact is a numeric field that usually needs to be aggregated, and will be set as the value part of visualizations. Examples of Facts are Sales Amount, Order Quantity, Profit, Cost, etc. A fact table is a table full of those fields.

Learning about building Tables manually.

Power Query has a simple way of calculating the age. However, because DAX is the popular language in many calculations in Power BI, many are not aware of this function in Power Query. In this blog article, I am going to show you how easy is to calculate Age in Power BI using Power BI. This method is very useful when the age calculation can be done on a pre-calculated row-by-row basis.

Accessing Extract Function in Power BI

In the query editor, you have two options when using the Extract function. You can access the 'Extract’ function from the “Add Column” menu

The other way to select the “Extract” function is via the “Transform” which is in the top menu as shown below.

DAX is a collection of functions, operators, and constants that can be used in a formula, or expression, to calculate and return one or more values. Stated more simply, DAX helps you create new information from data already in your model.

A calculated column is a column that you add to an existing table in the Data Model of your workbook by means of a DAX formula that defines the column values. Instead of importing the values in the column, you create the calculated column.

There is another way of defining calculations in a DAX model, useful whenever you do not want to compute values for each row but, rather, you want to aggregate values from many rows in a table. These calculations are measures. This is the same name used in the user interface, with the exception of Excel 2013, which uses the term “calculated field” instead of “measures”. Excel 2016 reverted back to “measures”, which is the term used in DAX and originally used in Power Pivot for Excel 2010, too.

AddColumns is a DAX function that is helpful often when writing calculations in Power BI. In this article and video, I’ll explain how you can use it to add calculated columns on the fly to the virtual tables in measures or directly in a table.

Power BI can provide the opportunity of leveraging AI with its features such as Quick Insights which helps in finding data patterns, or natural language which helps in finding answers by asking questions in simple English.

Microsoft has introduced new AI capabilities in Power BI. Now, users can leverage AI in business intelligence and can explore data, find answers, and identify patterns more easily. Here are what users can get with the new AI features in Power BI which requires no code:

1. Image recognition and text analytics directly in Power BI

2. Key Driver Analysis can provide insights on what drives key business metrics

3. Seamless integration of Azure Machine Learning within Power BI

4. Automated machine learning feature can help users create machine learning models directly in Power BI