How to use Power BI Desktop free tools with descriptive details

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Table of Content:
Describe Power BI:
Open-source tools highlighted
Architecture for integrating external tools:
Modeling operations for data:
Power BI is used by who?
Benefits of Power BI:
The shortcomings of Power BI:

Describe Power BI:

With the help of the business intelligence and information visualization tool Power BI, you can create a dynamic dashboard and analysis reports using data from numerous sources. With Power BI, customers can easily generate their dashboards and reports using a cloud-based service for interactive visualizations. For various platforms, several Power BI versions, including desktop, service-based (SaaS), & mobile Power BI apps, are employed. It offers numerous business intelligence software connections and services. Accessibility to external tools which have been locally installed and verified with Power BI Desktop is made simple via the External Tools ribbon. When a tool is started first from the External Tools ribbon, Power BI Desktop sends the name, port number, and current model name of its own internal data model engine instance.

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The tool then initiates an automatic connection, ensuring a seamless connection process.

Typically, external tools fit into any of the categories listed:

• Open-source applications like DAX Studio, ALM Toolkit, Tabular Editor, & Metadata Translator augment Power BI Desktop features for particular data modeling scenarios including DAX query and expression optimization, ALM, and metadata translation. Semantic modeling
• Tools for querying data and carrying out various analysis tasks can be connected to a model in read-only mode for data analysis. Tools that, for testing and analysis, link the client software to the model in Power BI Desktop without first publishing the Power BI Desktop (pix) file towards the Power BI service are examples of this. This category also includes tools for Power BI dataset documentation.
• Other - Some third-party products don't even connect to a model; instead, they expand Power BI Desktop to provide useful advice and other helpful stuff more available. For instance, the PowerBI.tips Product Business Ops community feature, the DAX Guide from sqlbi.com, and the PBI.tips tutorials all make it simple to install a variety of external tools and register them with Power BI Desktop. These applications include DAX Studio, ALM Toolkit, Tabular Editor, and numerous others.
• Custom - By including a *.pbitool.JSON file in the Power BI DesktopExternal Tools folder, you may integrate the business's scripts and tools. Take into consideration the following before installing external tools: Power BI Desktop for Power BI Report Server does not support external tools. External, outside third-party contributors offer external tools. Microsoft does not offer assistance or guidance for third-party tools.

Open-source tools highlighted
There are a lot of external tools available. A Power BI Desktop data modeler should have the following in their toolbox:

• PowerBI.tips - Business Ops: A simple deployment mechanism for Power BI Desktop extensions of external apps. Business Ops aim to give users a single location to download the most current editions of external tools.
• Tabular Editor: Tabular models can be readily built, maintained, and managed by model creators utilizing an easy-to-use editor. In a hierarchical view, which supports multi-select property editing with DAX syntax highlighting, all of the items in your tabular model are arranged by display folders.
• Dax Studio: A powerful tool with lots of features for DAX analysis, diagnostics, and performance adjustment. DAX syntax highlighting & formatting are included, along with embedded tracing, query processing breakdowns including extensive data, and object browsing.
• ALM Studio: An application lifecycle management (ALM) scenario-specific schema comparison tool for Power BI models and datasets. Simple deployment between environments is possible, and you can keep previous data for an incremental refresh. Branching, merging, and diffing metadata files are all possible. The definition of “ between datasets can also be reused.
• Metadata Translator: Simplifies the process of localizing Power BI models & datasets. Utilizing Azure Cognitive Services' machine translation technology, the tool could automatically translate table, column, measure, hierarchy captions, and descriptions, including display folder names. Additionally, Comma Separated Values (.csv) files can be used to export and import translations for convenient mass editing in Excel or a localization program.

Architecture for integrating external tools:
The report canvas, visualizations, model information, and any data that has previously been downloaded from data sources are all parts of Power BI Desktop (pix) files. An Analysis Services process is started in the background whenever Power BI Desktop opens a pix file to load the model for an order for the data modeling features and the report visualizations can access model information and query model data. 

Power BI Desktop dynamically allocates a random port number & loads the model with such a randomly created name throughout the form of either a worldwide unique identifier when it begins Analysis Services as its appropriate data engine (GUID). It can be challenging for external tools to figure out on their own which Analysis Services instance & model to link to because these connection settings vary with each Power BI Desktop session. This issue is resolved by external tools integration, which enables Power BI Desktop to send the Analysis Services server name, destination port, and tool name as command-line parameters to the external tool when initiating it from the External Tools ribbon.

The method utilizes Analysis Services client libraries to connect to the model, obtain information, and run DAX or MDX queries using the Analysis Services Server name, port number, & model name. Power BI Desktop synchronizes changes made to the metadata whenever an external data modeling tool modifies a modification, ensuring that perhaps the Power BI Desktop user interface appropriately reflects the model's current state. Remember that the synchronization capabilities have some restrictions, as explained below.

Modeling operations for data:
Modifications can be made using external data modeling tools, and Power BI will synchronize those changes well with the report canvas. This synchronization ensures that those changes are applied uniformly in Power BI visuals. For instance, external data modeling tools can modify any measure property, such as KPIs and detail rows, and can replace a measure's original format string expression. Additionally, other tools can provide translations and new roles for object & row-level security.

Operational write support

• Define and modify the parameters for the format string, and KPI, including detail rows used in computations.
• In order order order to reuse calculations in complex models, add calculation groups.
• To define specialized, business-domain-specific views of dataset metadata, and creative perspectives.
• To support multilingual versions inside the same dataset, use metadata translations.
• To limit access to the data, add dataset roles for the row-level security (RLS) & object-level security (OLS) rules.

Power BI is used by who?
Here is a significant professional who makes use of the Power BI tool: Business & Data Analyst; Developer & Database Administrator; IT Team; IT Professional; Consumer for End User Report; Data Scientist; PMO - Project, and Portfolio Manager

Benefits of Power BI:

• Provides prebuilt reports and dashboards for SaaS solutions.
• Update the dashboard in real time.
• Secure and trustworthy connection to your on-premises or cloud-based data sources
• Efficient utilization, hybrid configuration, as well as a secure environment are all features of Power BI.
• Querying data using natural language.
• Dashboard visualization feature
• Excel users will like the often-introduced new features.
• Several database connectivity options Q&A sections are published online.
• Integration of graphics including both Python and R scripting.
• Power Query offers a wide range of tools for cleaning and wrangling data.
• After uploading the data in Power BI, the web service can automatically schedule a refresh.
• Power BI is supported by the superpower of machine learning and artificial intelligence.

The shortcomings of Power BI:

• Users who have the same email domains are the only ones who can access the dashboards and reports.
• Imported data that is accessible through real-time connections will not be mixed by Power Bl.
• Power Bi won't accept zip files that are compressed using the data from an X-velocity in-memory database or files larger than 250MB.
• The maximum file size that Power BI will accept is 1 GB.
• User, account, or even other entity parameters are never accepted or passed by dashboards.
• There are very few data sources that allow connectivity to Power BI dashboards and reports in real-time.

Business intelligence (BI) enables you to evaluate data and deliver useful information that aids corporate executives and business managers in making strategic business choices.

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