In Power BI, you can store mainly two types of data.
Fact Tables:
The central table in a star schema of a data warehouse is a fact table that stores quantitative information for analysis, which is not normalized in most cases.
Dimension Tables:
It is a table in the star schema which helps you to store attributes and dimensions which describe objects that are stored in a fact table.
Increment refresh is a newly added data so that there is no need to truncate or load the entire data.
If you want to calculate numeric values, then use MAX. However, if it is for non numeric values, then you should use MAXA.
The Power BI data sources are extensive, which are divided as follows:
Files: Data can be imported from Power BI Desktop files (.pbix), Excel (.xlsx, xlxm), and Comma Separated Value (.csv).
Content Packs: It refers to the collection of related files or documents that are stored as a group. There are two types of content packs in Power BI: those from service providers including Google Analytics, Salesforce, or Marketo, and those created and shared by other users in the organization.
Connectors: To connect databases and other datasets, including Database, Azure SQL, and SQL Server Analysis Services tabular data, etc.
Power BI utilizes two built-in map charts map and a filled map. A filled map shows data points with geospatial areas rather than points on a map. Areas can be continent, country, state, city. Working with a filled map, however, is not as easy and convenient as the map chart is
The sum function (Sum()) takes the data columns and aggregates them totally but the SumX function (SumX()) lets you filter the data which you are adding.
SUMX(Table, Expression), where the table contains the rows for calculation. Expression is a calculation that will be evaluated on each row of the table.
It is the main engine which is used in power pivot. It allows you to load the large set of data into Power BI data.
Bookmark in Power BI helps you to capture the configured view of a report page in a specific time. This includes filter and state of visual which can use a short cut to come back to the report that you can add as a bookmark.
It is a calculating expression of DAX which allows calculation on data stored in a new column.
Alert works on data that is refreshed, Power BI looks for an alert, and it reaches the alert threshold or the limit then the alter will be triggered.
On-premise gateway acts as a bridge which helps you to transfer the data, which is on-premise (not on the cloud) safely and securely.
Tile is an important feature of power BI services and can be said as a picture of the data which can be pinned to the dashboard.
You can configure an automatic refreshing of data daily or weekly, and at different times. You can schedule only one refresh maximum daily unless you have Power BI Pro. In the Schedule Refresh section, simply use the pulldown menu choices to select a frequency, time zone and time of day.
Visual-level filters filter data within a single visualization. Page-level filters work on an entire page in a report, and different pages can have different filters. Report-level filters filter all the visualizations and pages in the report.
Steps to go to Data Stories Gallery:
* First, open PowerBI.com in a favorite browser.
* By hovering on Learn
* Click on Community
* Scroll down little, and you will find Data Stories Gallery.
* Anyone can submit her or his Data Story as well.
Data types of Dax are: 1) Numeric, 2) Boolean, 3) DateTime, 4) String, and 5) Decimal.
Power Map can display visualizations that are geographical in nature. Therefore, some kind of location data is needed—for example, city, state, country or latitude and longitude.
You can configure an automatic refreshing of data daily or weekly, and at different times. You can schedule only one refresh maximum daily unless you have Power BI Pro. In the Schedule Refresh section, simply use the pulldown menu choices to select a frequency, time zone, and time of day.
Visual-level filters filter data within a single visualization. Page-level filters work on an entire page in a report, and different pages can have different filters. Report-level filters filter all the visualizations and pages in the report.
This is the programming language used in Power Query. It’s a functional, case-sensitive language that’s similar to other programming languages and easy to use.
This is when steps defined in the Query Editor are translated into SQL and executed by the source database, instead of by your own device. It helps with scalability and efficient processing.
On a report page, you can resize a responsive slicer to different sizes and shapes, and the data contained in it will be rearranged to match. If a visual becomes too small to be useful, an icon representing the visual takes its place, saving space on the report page.
Power BI Desktop groups the data in your visuals into chunks. You can, however, define your own groups and bins. For grouping, use Ctrl + click to select multiple elements in the visual. Right-click one of those elements and, from the menu that appears, choose Group. In the Groups window, you can create new groups or modify existing ones.
* All
* File
* Database
* Power BI
* Azure
* Online Services
* Other
Filters sort data based on the condition applied to it. Filters enable us to select particular fields and extract information in a page/visualization/report level. For example, filters can provide sales reports from the year 2019 for the Indian region. Power BI can make changes based on the filters and create graphs or visuals accordingly. Types of filters are:
* Page-level filters: These are applied on a particular page from various pages available within a report.
* Visualization-level filters: These are applied to both data and calculation conditions for particular visualizations.
* Report-level filters: These are applied to the entire report.
Power View can be used to download data to Excel as well as make nice transformations.
Example: Filter, merge multiple sources, calculate, etc.
Power View enables you to present the data in reports
Excel, Power BI datasets, web, text, SQL server, and analysis services.
You’d use a custom visual file if the prepackaged files don’t fit the needs of your business. Custom visual files are created by developers, and you can import them and use them in the same way as you would the pre-packaged files.
Power BI has two versions to use. Users can use the Power BI free version for free. However, there is also a Power BI Pro subscription version, which can be purchased from Microsoft Store. The purchased subscription provides an enhanced version of various features available with the free Power BI account. Most business users use the subscribed account as it offers more data refreshers per day and other features than the free version.
Power BI is one of Microsoft's greatest data analysis and visualization tool developed and maintained. It provides dashboards, datasets, and reports that are the heart of Power BI. They enable users to create personalized dashboards combining cloud-born and on-premises data in a single view. It also allows monitoring the most important data enterprise-wide and from all their business apps. So, we can say that Power BI has a great impact on business intelligence and data analysis.
Power BI is Microsoft's tool for data analysis and visualization. It doesn't require knowledge or experience of any programming language. A data analyst can quickly connect with any data source, summarizing the findings into simple reports without any programming experience. With Power Pivot built into the Power BI, analytics measures were developed using DAX query language from Microsoft.
GetData offers data connectivity to various data sources. Connect data files on your local system. The supported data sources are:
* File: Excel, Text/CSV, XML, PDF, JSON, Folder, SharePoint.
* Database: SQL Server database, Access database, Oracle database, SAP HANA database, IBM, MySQL, Teradata, Impala, Amazon Redshift, Google BigQuery, etc.
* Power BI: Power BI datasets, Power BI dataflows.
Azure: Azure SQL, Azure SQL Data Warehouse, Azure Analysis Services, Azure Data Lake, Azure Cosmos DB, etc.
* Online Services: Salesforce, Azure DevOps, Google Analytics, Adobe Analytics, Dynamics 365, Facebook, GitHub, etc.
* Others: Python script, R script, Web, Spark, Hadoop File (HDFS), ODBC, OLE DB, Active Directory, etc.
The major differences between Power BI and Tableau are:
* While Power BI uses DAX for calculating columns of a table, Tableau uses MDX (Multidimensional Expressions).
* Tableau is more efficient as it can handle a large chunk of data while Power BI can handle only a limited amount.
* Tableau is more challenging to use than Power BI.
Content packs are packages comprising different Power BI objects such as reports, dashboards, datasets, etc. The two types of content packs are:
Service provider content packs: Service providers such as Google Analytics, Salesforce, etc. provide pre-built content packages
User-created content packs: Users can create their content packages and share them within the organization.
Microsoft Power BI is mainly used by the following:
<> Business & Data Analyst
<> PMO - Project Management Office
<> Developer & Database Administrator
<> IT Team, IT Professional
<> Consumer for End User Report
<> Data Scientists etc.
* Power BI Desktop—for desktop computers
* Power BI service—an online SaaS (software as a service)
* Mobile Power BI apps—for iOS and Android devices
All of these can be used in conjunction. For example, you might create a report on your desktop, and then publish and share it online so that colleagues on mobile devices can read it.
Yes. There are two main reasons why you can have disconnected tables:
<> The table is used to present the user with parameter values to be exposed and selected in slicers .
<> The table is used as a placeholder for metrics in the user interface
No. There can be multiple inactive relationships, but only one active relationship between two tables in a Power Pivot data model. Dotted lines represent inactive relationships and continuous lines represent active relationships.
Power Pivot for Excel supports only single directional relationships (one to many), calculated columns, and one import mode. Power BI Desktop supports bi-directional cross filtering relationships, security, calculated tables, and multiple import options.
The major building blocks of Power BI are:
* Datasets: Dataset is a collection of data gathered from various sources like SQL Server, Azure, Text, Oracle, XML, JSON, and many more. With the GetData feature in Power BI, we can easily fetch data from any data source.
* Visualizations: Visualization is the visual aesthetic representation of data in the form of maps, charts, or tables.
* Reports: Reports are a structured representation of datasets that consists of multiple pages. Reports help to extract important information and insights from datasets to take major business decisions.
Dashboards: A dashboard is a single-page representation of reports made of various datasets. Each element is termed a tile.
* Tiles: Tiles are single-block containing visualizations of a report. Tiles help to differentiate each report
The dashboard is like a single-page canvas on which you have various elements to create and visualize reports created by analyzing data. It comprises only the most important data from the reports to create a story.
The visual elements present on the dashboard are called Tiles. You can pin these tiles from the reports to the dashboard. Clicking any element on the dashboard takes you to the report of a particular data set.
The data source is the point from which the data has been retrieved. It can be anything like files in various formats (.xlsx, .csv, .pbix, .xml, .txt etc), databases (SQL database, SQL Data Warehouse, Spark on Azure HDInsight), or form content packets like Google Analytics or Twilio.
Power BI is available in various formats:
* Power BI desktop: For the desktop version
* Power BI mobile app: For using the visualizations on mobile OS and share it
* Power BI services: For online SaaS
In power BI, you have various kinds of views viz:
* Data View: Curating, exploring, and viewing data tables in the data set. Unlike, Power Query editor, with data view, you are looking at the data after it has been fed to the model.
* Model View: This view shows you all the tables along with their complex relationships. With this, you can break these complex models into simplified diagrams or set properties for them at once.
* Report View: The report view displays the tables in an interactive format to simplify data analysis. You can create n number of reports, provide visualizations, merge them, or apply any such functionality.
Primarily, Power BI has two sources to store data:
* Azure Blob Storage: When users upload the data, it gets stored here.
* Azure SQL Database: All the metadata and system artifacts are stored here.
They are stored as either fact tables or dimensional tables.
To access the Power BI features, visualize data, or model them to create reports, you can simply download a desktop version of Power BI. With the desktop version, you can extract data from various data sources, transform them, create visuals or reports, and share them using Power BI services.
Four main refresh options are available in Power BI:
* Package/OneDrive refresh: This synchronizes Power BI desktop or Excel file between the Power BI service and OneDrive
* Data/Model refresh: This means scheduling the data import from all the sources based on either refresh schedule or on-demand.
* Tile refresh: Refresh the tiles’ cache on the dashboard every time the data changes.
* Visual container refresh: Update the reports’ visuals and visual container once the data changes.
Power BI is an amalgamation of these major components:
* Power Query (for data mash-up and transformation): You can use this to extract data from various databases (like SQL Server, MySql, and many others ) and to delete a chunk of data from various sources.
* Power Pivot (for tabular data modeling): It is a data modeling engine that uses a functional language called Data Analysis Expression (DAX) to perform the calculations. Also, creates a relationship between various tables to be viewed as pivot tables.
* Power View (for viewing data visualizations): The view provides an interactive display of various data sources to extract metadata for proper data analysis.
* Power BI Desktop (a companion development tool): Power Desktop is an aggregated tool of Power Query, Power View, and Power Pivot. Create advanced queries, models, and reports using the desktop tool.
* Power BI Mobile (for Android, iOS, Windows phones): It gives an interactive display of the dashboards from the site onto these OS, effortlessly.
* Power Map (3D geo-spatial data visualization).
* Power Q&A (for natural language Q&A).
Power BI is a strong business analytical tool that creates useful insights and reports by collating data from unrelated sources. This data can be extracted from any source like Microsoft Excel or hybrid data warehouses. Power BI drives an extreme level of utility and purpose using interactive graphical interface and visualizations. You can create reports using the Excel BI toolkit and share them on-cloud with your colleagues.
Power BI was introduced by Microsoft to combine the multiple data visualization features into one. Power BI is the new term for the data-driven industry and thus carries a lot of opportunities on its shoulders. It comes as a package of three major components:
* Power BI services
* Power BI Desktop
* Power BI mobile app
With these three components, Power BI lets you create a data-driven insight into your business. Based on various roles, you can leverage Power BI to your benefits like creating reports, monitor progress, integrate APIs, and many more.