The fundamental purpose of leveraging Business Intelligence tools is to understand trends and derive actionable insights from your data, allowing you to make more strategic and tactical business decisions. The popular features offered by Business Intelligence tools are Visual Analytics, Data Visualization, KPI Scorecards, and Interactive Dashboarding to name a few. They also allow users to leverage predictive analytics and automated reporting features on a self-service basis.
Microsoft offers several Business Intelligence tools to cater to your needs. In this article, you will learn about the 4 key Microsoft Business Intelligence Tools: Power BI, Power BI Embedded, Azure Analysis Services, and Azure Synapse Services in great detail.
What is a Business Intelligence Tool?
In layman’s terms, Business Intelligence tools are application software, involved in collating and processing unstructured data from external and internal systems. The results obtained from Business Intelligence tools help increase operational efficiency, identify market trends, zero in on new revenue potentials, and identify new business opportunities.
Business Intelligence tools like Power BI are generally used for business reporting of data and simple querying of results, but they can also combine various data analysis applications like OLAP (Online Analytical Processing), Cloud and software as a service Business Intelligence, real-time Business Intelligence, and location intelligence to name a few.
What is Microsoft BI?
Microsoft BI is a technology-driven Business Intelligence Tool developed by Microsoft that helps analyze and visualize raw data to produce actionable insights. It integrates Business Analytics, Data Visualization, and Best Practices to assist organizations in making data-driven decisions. It provides an easy-to-use interface for end-users to create their own Reports and Dashboards. You can leverage it to extract data from various Cloud and On-premise systems and build Dashboards that track the most important metrics to you and your business. Apple, Exxon Mobil, Walmart, and Toyota Motor North America are some of the prominent names that leverage Microsoft Power BI for Business Intelligence.
Understanding the Importance of Microsoft Business Intelligence (BI) Tools
The Microsoft Business Intelligence Suite is a suite of tools designed to make data processing easier. The complete range of tools helps businesses direct data through IT systems, create expansive reports on the current status of various departments, and identify and isolate data. It includes SSRS (SQL Server Reporting Services), SSIL (SQL Server Integration Services), and SSAS (SQL Server Analytical Services). Microsoft Business Intelligence platform functions by moving data from various disparate data sources to a centralized architecture where the rudimentary data can be reconfigured. Here are a few benefits of Microsoft Business Intelligence tools:
- Elimination of Manual Tasks: Previously, Business Management relied on static presentations and spreadsheets. Microsoft Business Intelligence tools eliminate the endless amount of columns & rows and facilitate the automation of processes. Be it a dashboard with real-time data or interactive presentations, Microsoft Business Intelligence tools have got you covered.
- Reduction of Business Costs: Microsoft Business Intelligence tools enable faster analysis, planning, and reporting processes for customer behavior analysis, sales planning, and real-time optimization. Since these tools bolster the efficiency of your operations, it helps you cut back on costs and make more profitable adjustments.
- Impeccable Support: The needs for each organization looking for a Business Intelligence tool are unique to their goals. Data storage in the cloud allows users to explore various self analytics features with a support system working 24*7 to resolve any issues they might come across.
- Key Predictions: Microsoft Business Intelligence tools allow any business user to generate actionable insights for future scenarios through the incorporation of forecast engines. This helps companies adjust current strategies to deliver the best possible results.
- Easy Data Access: By providing data access to every individual within a company, Microsoft Business Intelligence tools significantly reduce the need to request reports from the IT department. A self-service BI approach as mentioned here allows enterprises to gain a competitive edge. Since every employee is equipped with the appropriate data analytics skills, it helps save the company’s resources and time while easing the burden on the IT department. This frees up more time which can be focused on more critical tasks.
Types of Microsoft BI Tools
Power BI is not the name of a single application, but the umbrella term for a collection of applications. The types of Microsoft BI tools are explained in detail.
1. Power BI Desktop: It is the most basic application. As the name suggests, it can be installed in standalone mode on a desktop. It is offered free of cost and can be connected to various data sources. It enables users to analyze data and derive insights from the data. It can connect to on-premise as well as cloud-based data sources. Power BI Desktop is not available via the web and is an independent stand-alone analysis tool. Beyond the ad-hoc analysis tool use case, it also acts as the development environment for creating reports and dashboards that can be deployed later.
2. Power BI Report Server is a web application that can be deployed on-premise to let the users in an organization view the reports and dashboards. The reports and dashboards that are designed through the Power BI Desktop can be deployed in the report server. It supports a level of interactivity for the reports and dashboards.
3. Power BI Service is the cloud-based business intelligence tool that is available based on a subscription from Microsoft. It lets the users take advantage of Power BI Analytics features without having to spend time with deployment or maintenance. It can connect the most common on-premise and cloud-based data sources. In the back end, it works based on Microsoft Azure compute clusters. This enables it to handle large data volumes and streaming data. It is offered based on different subscription plans like premium and pro depending upon the feature sets.
4. Power BI Mobile is Microsoft’s attempt to bring Power BI to mobile devices. In the back end, it also makes use of the Power BI Service. All the actual data processing happens in cloud servers and the mobile application serves as the front end for displaying interactive dashboards and reports.
Power BI Embedded helps users to enable Power BI features in their custom web applications. It enables developers to control the user experience while letting their customers have access to the power of analytics in a familiar environment.
Microsoft Business Intelligence tools provide a convenient solution to handle the vast amount of crucial Business Intelligence information continually by modern companies. In this section, you will get a glimpse of the 4 key Business Intelligence tools that are a part of the Microsoft Business Intelligence Suite.
- Power BI
- Power BI Embedded
- Azure Analysis Services
- Azure Synapse Analytics
1. Power BI
Microsoft Power BI is the top Microsoft Business Intelligence tool that is a mix of SaaS, Cloud-Based, and Desktop tools. The central focus of Power BI is data mining, exploring, and reporting. Power BI is mainly used for achieving reporting tasks through APIs (Application Programming Interfaces). The elegance of Power BI comes from its near-limitless ability to mine data from diverse sources. It can extract insights from traditional databases as easily as it can extract data from newer SaaS architectures, for instance, GitHub and Zendesk.
Key Features of Power BI
Here are a few key features of Power BI that make it such as indispensable tool:
- Convenient Reporting of Data: You can start working on building elegant reports once the right data sources have been mined and relevant insights extracted. Power BI also supports third-party custom visuals.
- Transformation of Data: Once you have put aside the sources you want to import, Power BI gives you a preview window. In this preview window, you can choose columns or other classification features for better organization of data. The Query Editor allows you to change, shape, configure and restructure data in various ways.
- Discovery of Data: The primary purpose of Power BI is data mining. It looks for information in as many sources as instructed. You can do this by either importing data to Power BI or leveraging Direct Query, based on the size of your desired report.
- Creation of Dashboards: A key proponent of collaboration is a dashboard. It allows a user to view and interact with the report. Power BI is flexible enough to let you create a live report feed so that all memos and documents get uploaded to the dashboard.
Security Features of Power BI
Power BI is built on the back of Azure, Microsoft’s Cloud Computing platform and infrastructure. The Power BI service architecture is based on two clusters: the Back End cluster and the Web Front End (WFE) cluster. The WFE cluster focuses on the initial authentication and connection to the Power BI service, while the Back End cluster deals with all the subsequent user interactions.
User Identities are stored and managed by Power BI by utilizing Azure Active Directory (AAD). The data storage is managed by Azure BLOB and the storage of metadata is managed by leveraging Azure SQL Database.
Pricing of Power BI
There are two pricing plans offered by Microsoft for Power BI:
- Power BI Pro: $9.99/user/month
- Power BI Premium: This plan has two subsequent plans:
- Per User: $20/user/month
- Per Capacity: $4995/user/month
2. Power BI Embedded
Power BI Embedded is a Platform as a Service (PaaS) offering that enables developers to embed dashboards and reports to an application for their customers. Power BI Embedded allows you to build top-notch analytics without having to develop them yourself. With Power BI Embedded, you can reduce developer resources by automating the management, monitoring, and deployment of analytics.
Key Features of Power BI Embedded
The embedding is carried out through an hourly metered, capacity-based model. Coupled with a REST API, Power BI Embedded lets you develop elegant apps in any language. Here are a few features of Power BI Embedded:
- Control User Experience: With hundreds of visuals to choose from, Power BI Embedded ensures you have full control over how to deliver analytics to your users. It does this through several actions like:
- Turning on Q&A sessions to ensure users get their answers immediately.
- Using your brand colors so that visuals match your application.
- Customization of the analytics menu with desired actions for your users.
- Faster Business Growth: Power BI Embedded helps you create differentiated offers, new revenue streams, and data products to improve customer interactions and get to market faster.
- Easy Management and Deployment: This Microsoft Business Intelligence tool makes it incredibly easy to deploy and manage through the following features:
- Performance monitoring and automation with REST APIs.
- Providing the best user experience by scaling to meet the needs of the users.
- Easily embed with JavaScript SDK.
- Customized Visualizations: You can adopt the best way to visualize data with out-of-the-box, custom-built and certified visualizations. The users can make decisions from anywhere with visualizations optimized for mobile and desktop.
Security Features of Power BI Embedded
Power BI Embedded takes user security very seriously. This is evident from the following features of Power BI Embedded that ensure a secure and robust front when it comes to data security:
- It keeps user information secure by managing all the authentication and identity on your end.
- Power BI Embedded restricts user access with row-level security. This means that users can only view data that is relevant to them.
Explore more about : Xero Power BI Integration.
Pricing of Power BI Embedded
The total cost of Power BI Embedded depends on the number of nodes deployed and the type of node you choose for your operations. The node types differ based on RAM and the number of V-cores as follows:
3. Azure Analysis Services
Azure Analysis Services is a Platform as a Service (PaaS) offering that provides enterprise-grade data models in the Cloud. It also allows you to host semantic data models and leverage modeling features and advanced mashup to combine data from various sources.
Key Features of Azure Analysis Services
Azure Analysis Services can be used to define metrics and secure your data in a trusted tabular data model. This data model provides a faster and easier way for users to perform ad hoc data analysis using tools like Excel and Power BI. Here are a few key features of Azure Analysis Services:
- Accelerated Time of Delivery: With this Microsoft Business Intelligence tool, you can deploy your solutions, in a highly secured and predictable way. You can leverage robust application lifecycle management capabilities to deploy, govern, test, and deliver your BI solution quickly and with confidence.
- Development in a Familiar Environment: Azure Analysis Services help you focus on solving business problems with a familiar integrated development environment of Visual Studio. You can also easily deploy any of your existing SQL Server tabular models to the Cloud.
- Complex Data Transformation: You can combine data from various sources into a single BI semantic data model for simplification. You can enable data discovery and self-service for business users with a simple view of data.
- Faster Performance: With Azure Analysis Services, you can greatly reduce the time it takes to extract insights from large and complex datasets. A faster response time indicates that your BI solution is competent enough to meet the needs of your business users while staying on top of their business proceedings. To connect with real-time data you can use Direct Query.
- Quick Scale-Up: You can use Azure Resource Manager to create and deploy an instance of Azure Analysis Service within seconds. You can also use the backup restore feature to move your existing models to Azure Analysis Services and utilize the flexibility, management benefits of the Cloud. You can scale down, scale up or pause this Microsoft Business Intelligence offering whenever you want and pay for what you use.
Security Features of Azure Analysis Services
Here is why Azure Analysis Services should be trusted to handle your data operations:
- Over 3,500 security experts strive every day to provide you with dedicated data privacy and security.
- You can make sure only authorized users can access your data models with Azure Active Directory Support and role-based security. Boasting a 99.9% availability, your users can easily access critical information when they need it.
Pricing of Azure Analysis Services
Azure Analysis Services offers three tiers to choose from. The pricing for the three tiers will depend on the chosen tier and instance. Within each tier, the prices will differ by QPUs, processing power, and memory size.
- Developer Tier: This tier has just one instance. This is depicted as follows:
- Basic Tier: The Basic tier offers two instances to choose from as follows:
- Standard Tier: The Standard Tier offers 8 different instances to choose from. This is depicted as follows:
4. Azure Synapse Analytics
Azure Synapse Analytics is a veritable analytics service that weaves together Enterprise Data Warehousing, Big Data Analytics, and Data Integration. You can utilize serverless or dedicated resources to query data on your terms, at scale.
Key Features of Azure Synapse Analytics
Azure Synapse Analytics is being widely used in industries like Manufacturing, Retail, Healthcare, and Financial Services with personalized features for each industry that optimizes the operations of any company that uses it. Here are a few key features of Azure Synapse Analytics:
- Data Lake Exploration: With this Microsoft Business Intelligence offering, you can bring together relational and nonrelational data while querying files in the Data Lake with the same service used for building data warehousing solutions.
- Code-Free Hybrid Data Integration: You can build ETL/ ELT processes from over 95 native creators in a visual, intuitive, code-free environment to easily ingest data.
- Integrated AI and BI: For a complete end-to-end analytics solution, you can establish integrations with Power BI, Azure Cognitive Services, and Azure Machine Learning.
- Apache Spark and SQL Engines Integration: The integration with Apache Spark and SQL Engines allows you to easily use T-SQL queries on your Spark Engines and data warehouse to enhance collaboration on advanced analytics solutions.
Security Features of Azure Synapse Analytics
Here is how Azure Synapse Analytics ensures total security:
- End-to-End Management and Monitoring: Azure Synapse Analytics works on securing the Synapse workspace with end-to-end management and monitoring to provide a robust and unified data analytics platform.
- Azure Active Directory Integration: You can use single sign-on and Azure Active Directory Integration to allow data professionals to spend more time gathering and discovering insights.
Pricing of Azure Synapse Analytics
There are pricing plans for data pipelines, data flows, and operation charges. This is depicted as follows:
- Data Pipelines: There are 4 kinds of pricing plans for any Data Pipeline you wish to work within Azure Synapse Analytics as follows:
- Data Flows: There are 3 pricing plans for Data Flows as follows:
- Operation Charges: The Data Pipeline Operations namely update, read, delete, etc. will be charged from 1 Feb 2021. The first 1 million operations per month would be free, after which you will be priced at $0.25 for every 50,000 operations.
Microsoft’s Other Business Intelligence Tools
It’s easy to forget that there are other MS BI solutions when Power BI provides so many distinct data processing functions. It’s part of a collection of tools, many of which can be used as SQL Server Integration Services Sources (SSIS). They help with data extraction and integration in order to provide usable, useful Business Intelligence.
SharePoint, for instance, is a web-based platform that allows users to create Collaborative Workflow. It recognizes and saves important files so they may be moved to a Microsoft BI software interface at your leisure. Because many corporate technologies are going towards totally virtual architectures, cloud-based apps are just as crucial.
Since it speeds up the transportation of data through Microsoft-based software processes, Azure is a big hit for the company. It’s a flexible architecture that allows you to build Cloud-native apps. Azure may be used in conjunction with Power BI and other apps to create more self-contained data platforms that are not limited by hardware.
It offers a variety of cloud services, such as computing, analytics, storage, networking, integration, and development. These services are available to users who want to develop or grow new applications or run existing ones in the public cloud.
Working with the cloud has numerous benefits, including the ability to minimize on-premise workloads. In theory, there are no storage constraints. Furthermore, security measures are updated on a regular basis without your input. One of the most significant advantages of the cloud is that it is always evolving in reaction to new information and capabilities.
How to Use Excel for Business Intelligence?
There may be moments when you wish to simplify the process and return to the fundamentals. In any case, it’s a good idea to keep an eye on Excel and familiarise yourself with its primary features. Of course, one of the most significant advantages of utilizing Excel is its low cost. There are rarely any hidden fees, and it remains one of the most affordable software solutions available.
It’s also quite simple to learn, which makes it an excellent foundation for new enterprises. Users with little training will find it less daunting because most people have used it at least once before. You can also construct dashboards with it, similar to Power BI. For the reasons stated, the interface isn’t always as seamless, but Excel is still capable of manipulating massive amounts of data.
It’s a good idea to get the PowerPivot add-on if you wish to utilize Microsoft Excel for self-service Business Intelligence. This is how you’ll be able to create custom dashboards. It’s here that you can share and pin reports derived from various data sources. There’s also a robust data reporting feature that allows for complex DAX calculations.
Alternatives to Microsoft BI Tools
1) Tableau
Tableau is the leading Business Intelligence and Data visualization Tool in 2021. It has several in-built connectors to connect to various sources, thereby creating visual masterpieces with a perfect blend of symbolic elements like colours, tables, and charts that help businesses implement data-driven decisions. Some key features of Tableau are as follows:
- Tableau is a Reporting Tool with an intuitive dashboard with thousands of symbolic elements to create visuals.
- Tableau enables users to securely collaborate on the worksheets and dashboards with peers and leaders for design suggestions and review.
- Tableau offers excellent support for real-time data integration. It also encompasses robust In-memory Computation.
- Tableau has over 200+ connectors available in its library, which can connect to any Relational and Non-relational Database, CSV and Excel files, Hive, Snowflake, etc.
Learn how to unlock insights with the Tableau semantic layer by reading our blog.
2) QlikView
QlikView is a classic Reporting Tool that provides analytical solutions and allows you to develop appealing visualization from the data. It is an Enterprise Tool that converts raw data into a meaningful format. Some features of QlikView are as follows:
- Unlike other dashboarding tools, QlikView stores the data in memory for super-fast analysis.
- It supports scalability and provides consistent reporting.
- It contains ample templates and supports various forms of data presentation.
- It provides Data Discovery and the utmost security to the data.
3) Looker
Looker is a Reporting Tool part of Google Cloud that allows users to perform analysis on live data with a built-in modelling language known as LookML, a variant of SQL. Looker has Git Integration to extend and enhance SQL based analysis. Looker generates real-time snapshots with the data based on SQL queries and can be used when you want to perform complex analyses with big datasets to generate on-the-spot reports. Some key features of Looker are as follows:
- Looker allows around 12 different types of filters to analyze the data at the most granular level.
- Looker allows cross-filtering on live data with simple clicks on the dashboard points. This allows users to perform an in-depth analysis on-the-fly.
- Looker has cross integration with different apps that allow users to set actions and Webhooks for automated alerts and notifications.
Conclusion
This blog talks in detail about the different Microsoft Business Intelligence tools that the software giant has to offer. For each of the tools discussed here, the features, security measures, and pricing are highlighted.
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FAQs
1. What is Microsoft business intelligence?
Microsoft Business Intelligence (BI) refers to a set of tools and technologies that help businesses collect, analyze, and visualize data to make informed decisions. It includes products like Power BI, SQL Server Reporting Services (SSRS), and SQL Server Analysis Services (SSAS) that enable data integration, reporting, and analysis.
2. What is the difference between Excel and business intelligence?
Excel is a powerful spreadsheet tool primarily used for data analysis and basic reporting, while Business Intelligence (BI) refers to a broader set of tools and technologies that enable data integration, advanced analytics, and interactive reporting. BI tools like Power BI offer more robust features for data visualization, real-time insights, and scalability compared to Excel.
3. How much does a business intelligence analyst make at Microsoft?
The salary for a Business Intelligence (BI) Analyst at Microsoft typically ranges between $80,000 to $120,000 annually, depending on factors such as experience, location, and role responsibilities. In some cases, more experienced analysts or those in higher-level positions can earn up to $140,000 or more. For the most precise figures, checking dedicated salary websites or Microsoft-specific job listings would provide the best insights.
4. How much do Microsoft business intelligence engineers make?
At Microsoft, business intelligence engineers earn an average salary of around $130,000 annually, which includes base pay and additional compensation like bonuses or profit sharing. However, salaries can vary depending on experience, location, and the specific team within Microsoft. Some sources report base salaries of about $111,000, with additional pay adding up to $19,000
Amit is a Content Marketing Manager at Hevo Data. He is passionate about writing for SaaS products and modern data platforms. His portfolio of more than 200 articles shows his extraordinary talent for crafting engaging content that clearly conveys the advantages and complexity of cutting-edge data technologies. Amit’s extensive knowledge of the SaaS market and modern data solutions enables him to write insightful and informative pieces that engage and educate audiences, making him a thought leader in the sector.