Everything You Need to Know about Microsoft Business Intelligence Tools

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We’re truly living in the age of big data. For modern businesses, information is everything. Microsoft BI tools provide a solution for handling the volume of important business intelligence information continuously generated by modern companies.

With the right tools, you can process huge amounts of data in mere seconds, and it is this part of the process that counts. Any business can collect information, but it takes skill and careful management to make it valuable.

This is the essence of “business intelligence”: the ability to take vast quantities of market data and extract trends and patterns.

Fortunately, business intelligence software has grown increasingly sophisticated over the years. It is capable of processing and collating data from a hundred different sources so your company has the best possible view on the market. The Microsoft Business Intelligence suite is one such solution, and it offers a comprehensive array of functions and features.

What is Microsoft BI?

Microsoft BI tools are designed for easy data processing. That’s putting it a bit simply, but these programs do have a simple objective. The system aims to help businesses turn all of that messy, complex information into extractable insights. It is one of the most popular BI solutions on the market right now.

The full range of tools enables businesses to direct data through IT systems, identify and isolate data, and create expansive reports on the current status of different departments. They include SSIL (SQL Server Integration Services), SSAS (SQL Server Analytical Services) and SSRS (SQL Server Reporting Services).

With these tools, any mass of data can be turned into a digestible report, dashboard, graph, spreadsheet or another format. You just need to input your parameters and let the system know what you need. Microsoft BI software works by moving data from multifarious, unmanageable sources to a centralized architecture where it can be reconfigured.

Why is Power BI Important?

The top Microsoft business intelligence tool is its innovative Power BI service. It’s a curious mix of SaaS, desktop and cloud-based tools.

The different products offered by Microsoft are: Power BI Desktop, Power BI Pro, Power BI Premium, Power BI Mobile, Power BI Embedded and Power BI Report Server. Power BI Desktop is the software’s free program, intended for businesses in need of a low-cost report building tool.

Desktop is able to connect to a broad range of databases and various on-premise and cloud-based sources such as Salesforce, Dynamics 365, Excel, Azure SQL DB. It also publishes visualizations on public online spaces, such as the Power BI service.

Power BI Pro is the next step up. Pro gives users more control over report sharing, with features that enable role-specific data protection, project collaboration and simplified circulation. Power BI Premium is the suite’s top-tier solution. It is made for large-scale data analysis, increased distribution ability and more options for deployment.

Power BI mobile lets you view live dashboards and reports on mobile devices and share them directly with team members from the app. Power BI Embedded allows you to deploy analytics and ensures data security in single and multi-tenant deployments. Power BI Report Server allows you to publish reports on the server and share them with other users.

The central focus of the system is reporting, data mining and exploring. It is able to pinpoint valuable data from a variety of sources and build it up into a report or combine it with others.

Power BI is especially useful for accomplishing reporting tasks through application programming interfaces (APIs). In many ways, Power BI is much like the existing SSRS framework of Microsoft Business Intelligence. It creates intricate layers of data which contribute to the final reporting aspect of business intelligence operations.

The desktop app is great for drawing up and publishing reports. This part of the system is well suited to extracting initial insights. In other words, it can help you determine which questions you need to answer.

To put it another way, your data holds the answers to every question about your business. However, this is far more of a frustration than an asset, unless you decide which questions and answers are valuable. Power BI can help you do this by connecting to live data and providing real-time analytics of trends and market indicators.

The real beauty of Power BI is its near-limitless capacity to mine diverse sources. It can extract insights from much newer SaaS architectures (like Zendesk and Github) just as easily as it can from traditional databases. You can even link the software up to statistical language and have it display complex numerical reports.

The Key Features of Power BI and Why You Need Them

Finding Data

As we’ve discussed, the primary purpose of Power BI is data mining. It searches for information in as many different sources as you tell it to. There are two main methods for achieving this. You can import the data to Power BI, or you can rely on Direct Query. If you choose to import, you’ll be limited to viewing 1GB of information at any one time.

This can be frustrating, but the solution is to use Direct Query for larger reports. Although, you should be aware that Microsoft Direct Query isn’t compatible with all data types. You can check whether yours is one of them by visiting this list of approved sources. New sources are added frequently.

If neither of these methods is suitable, Power BI Premium is intended for much larger reports.

Transforming Data (Query)

After you’ve picked sources to import, Power BI gives you a preview window. This is a chance to choose columns or other classification features to help you better organize the data. The Query Editor is a very interesting tool because it allows you to shape, change, configure and restructure the data in multiple ways.

Reporting and Publishing

Once the right data sources have been mined and relevant insights extracted, you can start drawing up custom reports. There are a lot of different ways to present information, but the most common are elements such as pie and line charts. Basically, the simpler it looks on a page, the easier it will be to utilize and share.

Calculated columns and measures are accessible via Digital Analysis Expressions (DAX). Power BI also supports the use of third-party custom visuals. You can, of course, publish reports to the Power BI service once they’re ready. You need a registered account for this, but all Power BI Desktop, Pro and Premium users should have valid credentials.

Creating Dashboards

The dashboard is a useful function for sharing. It allows you to control who views and interacts with the report. You can make it “sticky,” so it remains in a visible place. Or, you can just highlight important bits and pin those to your virtual board. You also have the option to create a live report feed, so all documents and memos get uploaded to the dashboard.

Depending on whom you want to see the report, you can switch certain permissions on or off. For instance, you can allow department heads to view and index information. They can highlight key details by selecting slicers and filters.

Sharing and Collaborating

Unsurprisingly, Microsoft Business Intelligence software has robust security features. They’re very flexible and customizable, so users can structure levels of access. Ultimately, you do want managers and supervisors to have the freedom to view and edit reports. Often, this is the key to finding new forms of supply chain optimization.

As with all logistics software, Power BI has a central control function, so data management processes can be overseen at an executive level. In most businesses, however, multiple dashboards are set up for different departments, and they’re maintained by senior figures. The App Workspaces function is an easy way to share and collectively edit these dashboards.

On-Premise Data Gateway

One of the most clever Power BI tools is the On-Premise Data Gateway. This forms a permanent link between the data sources and your report. So, in theory, the report will continually update itself whenever new information is added, or the existing data is changed in some way. This is a vital function, as it will save you hours of time spent drafting reports.

To keep the data fresh, you need to install the Power BI On-Premise Data Gateway separately. It creates a secure connection between your local network environment (where your sources are) and the Power BI service. Once you have this, you can construct data refresh scenarios, which ensure new information is added according to your requests.

Power BI Mobile

These days, all business software needs to be mobile compatible. Fortunately, you can access Power BI on Windows, Android and iOS devices with the corresponding app. The functionalities aren’t quite as extensive, but you have everything you need for indexing data and creating reports on the move. Create mobile-optimized dashboards and reports with interactive drill-down/up capabilities.

Azure Integration

Power BI is compatible with various Azure data platform tools. They include data lakes, analysis services, HDInsight, machine learning, SQL and SQL data warehouses. The benefit of bringing the two together is Azure expands the reach of your software and opens up more opportunities for automation and cloud-based warehousing.

Flow and PowerApps

Microsoft business software, Flow and PowerApps, provide additional tools for dashboard organization and integration. They make it easier to establish parameters for reports and structure information in an optimal way. For instance, if you apply a threshold data alert for specific visuals on the dashboard, the system will launch a workflow when the target is reached.

Stream Analytics

Some businesses find themselves in need of faster, more dynamic reports. The Stream Analytics function is good for this because it supports the smooth streaming of information to the dashboard. It is becoming increasingly important for Internet of Things scenarios, as it can bring machine sensor data into the dashboard too.

Advanced Analytics

Facilitate advanced data analysis and manipulation by leveraging libraries and packages of Python and R programming languages. Conduct cluster analysis based on k-means, k-medoids, hierarchical clustering and other techniques to create segments or groups.

Create a regression model that describes the relationship between multiple independent variables and a single dependent variable to make predictions. It supports different types of regression analysis, including logistic, linear, multivariate, exponential and more.

Forecast future trends based on present and past data using forecasting methods such as moving averages, exponential smoothing, ARIMA, SARIMA and more. Use text mining to explore and analyze unstructured text data to identify trends, patterns, concepts, topics, keywords and more.

Data Visualization

Create dashboards that provide a single screen snapshot of KPIs, metrics and critical data points. Leverage drill-down and drill-up capabilities to explore multidimensional and hierarchical data. The drill-down capabilities help navigate from a high-level data view to a granular view in one click. The drill-up capabilities navigate back to the summarized view from a detailed one.

Create interactive data visualizations such as charts and graphs with advanced features like scaling, linking, tooltip, mouse and touch events. Embed these visualizations into external web pages. Leverage auto-charting capabilities to choose suitable visualizations for the graphical representation of selected data.

Data Management

Use data blending to combine multiple datasets into a single new dataset for analysis. Explore large unstructured datasets to unearth patterns, characteristics and points of interest and describe them using statistical and visualization tools and techniques. Prepare data for analysis by leveraging in-built tools for data pre-processing, profiling, cleansing, validation and transformation.

Conduct multidimensional analysis by supporting OLAP operations like slicing and dicing, roll-up and drill down. Leverage a metadata management tool to centralize metadata in a single location containing information about its location, profile, statistics, summaries and comments.

Data Querying

Facilitate batch updates by allowing users to request records and update them without maintaining a connection to the data source and send them back to the source. Conduct in-memory analysis by executing queries on data residing within memory instead of querying data stored on physical disks.

Run subqueries while using set operators (union, intersection and more) and calculated conditions in queries to form complex queries and extract relevant data. Maintain a direct live connection to the data source to perform data analysis. Query data from multiple sources, including OLAP, web services, relational, CSV, XML and more.

Augmented Analytics

Leverage machine learning capabilities to make predictions or find new segments or clusters automatically. Machine learning automation augments data profiling and quality, harmonization, modeling, manipulation, metadata development, cataloging and enrichment. Present insights such as variations, associations, correlations or trends in a dataset with augmented analytics capabilities.

Identify the best types of data or variables to build predictive models. Identify the key drivers or attributes of a given metric within the dataset. Use a text or voice-based search interface to search using natural language statements.

Embedded Analytics

Integrate interactive dashboards, reporting, data analysis and more into the embedding application. Configure workflow actions to trigger a workflow. Update multiple data sources in real time by initiating backend processes.

Geospatial Visualizations and Analysis

Facilitate forward and reverse geocoding to plot geographic locations on the map. Enable geographic calculations and functions to transform geospatial data and perform analysis. Visualize spatial data using interactive visualizations like proportion symbol maps, choropleth maps, heatmaps, flow maps, dual-axis maps and more.

Microsoft’s Other Business Intelligence Tools

With Power BI providing so many different data processing functions, it’s easy to forget that there are other MS BI tools. It is part of a suite of tools, many of which can be used as sources for SQL Server Integration Services (SSIS). They support the extraction and assimilation of data, with the aim of creating viable, practical business intelligence.

SharePoint, for example, is a web-based platform which builds collaborative workflows. It identifies and retains valuable files so they can be transferred out to a Microsoft BI software interface at a time of your choosing. Cloud-based applications are just as important, of course, because many business technologies are moving towards completely virtual architectures.

Azure is a hit for the vendor because it streamlines the movement of data through Microsoft-based software processes. It is a highly versatile system, with the ability to construct apps in a cloud-native fashion. Azure can be combined with Power BI and other programs to create more independent data systems, free of hardware limitations.

It provides different cloud services, including computing, analytics, storage, networking, integration, development and more. Users can choose from these services to develop or scale new applications or run existing applications in the public cloud.

Working with the cloud brings many advantages, including the opportunity to reduce on-premise workloads. There are, in theory, no limits on storage. And security protections are constantly updated without any contribution from you. This is one of the biggest advantages of the cloud — it is continually changing in response to new information and abilities.

The Relationship between Power BI and Excel

With so many dynamic tools to offer, it’s natural to wonder how the Microsoft Business Intelligence Suite might change your relationship with older, established programs. Microsoft Excel, for instance, has been at the forefront of logistics and supply chain operations for many decades. So, the question is, where does it stand now that Power BI is on the scene?

Well, you might not know that Power BI was originally born of Excel. It started life as an add-on for the program and used query tools to turn tabular data into graphs and charts. It was able to connect to the SQL Server OLAP tool to provide an easily-navigated interface for billions of columns worth of information. Now, Power BI has moved beyond Excel.

This doesn’t mean you should ditch your classic spreadsheets. Power BI might be a standalone analytics system, but it is modeled on the Excel way of working. The difference between the two is the integration of new and existing functionalities. Before Power BI, it was already possible to kit out Excel with a range of analytics and visualization features.

The value of the new tools – Power Query, Power Pivot, Power Map and Power View – has never been in doubt, but they don’t necessarily feel included in the primary interface. In fact, they all come with their own interfaces, so analyzing data with Excel is kind of like operating two, three or even four different systems. It works, but it isn’t very efficient.

Power BI brings all of the functions of Excel and the Power add-ons together in one cohesive software solution. The visual editing tools make it easy to reconfigure, edit, add and eliminate data. However, there’s no longer any need to jump between different interfaces. You can complete an entire data lifecycle (mining, reporting and presenting) without leaving the suite.

How to Use Excel for Business Intelligence

There may be times when you want to strip the process down and go back to basics. Either way, it’s useful to keep one eye on Excel and stay familiar with its main features. The big benefit of using Excel, of course, is it’s very affordable. It’s rare for there to be any additional costs, and it continues to be one of the most accessible software solutions.

It’s also extremely easy to master, which is why it provides a great foundation for new businesses. As most people have used it at least once before, it doesn’t feel so intimidating to users with minimal training. Plus, you can use it to create dashboards, similarly to Power BI. The interface isn’t always as smooth, for the reasons described, but Excel is still capable of transforming large quantities of data.

If you do want to use Microsoft Excel for self-service business intelligence purposes, it’s a good idea to download the PowerPivot add-on. This is what will allow you to construct custom dashboards. It is here where you can post and pin reports formulated from selected data sources. There is also a powerful data reporting function, which enables advanced calculations via DAX.

Creating a BI Dashboard with Microsoft Excel

With the dashboard tool in Excel, one example of functionality is the ability to display data relating to sales. You can pinpoint a specific timeframe and location for an accurate picture of your performance in that area. Whether it’s one, two or five years of information you need to analyze, the system can present it in an easily digestible format.

The Excel dashboard is handy for identifying key performance indicators and consolidating, organizing and interpreting multiple metrics on one page. With the PowerPivot, it becomes possible to create real-time links. As with Power BI, you forge a connection between the report and the live data sources so any changes are reflected there.

You’ll find the PowerPivot function inside Excel on its own tab. As already mentioned, it is not technically an integrated part of the program. It is an add-on and must be operated as such. Nevertheless, it allows you to import information from a database in seconds. All you have to do is write a query and wait for the data to be compressed and presented back to you.

The Best Alternatives to Power BI

It’s worth mentioning that the Microsoft BI suite isn’t the only one of its kind. It is certainly the most widely used, but this doesn’t mean it’s the best fit for every business. For instance, a common concern for potential users is whether this software has the technical capabilities to live up to its brand name.

Regardless of whether Power BI is as innovative as Microsoft claims, it’s obvious that being such an established brand is an advantage. Microsoft BI tools will always be popular because they have become synonymous with computing. If you don’t have much experience with administrative programs, you’re going to opt for a name that you recognize.

So, the question of whether Microsoft is the best provider available doesn’t have a clear answer. It depends on the needs of the user in question and whether the system’s architecture provides enough support for those needs. If you are unsure if Microsoft BI tools will be able to fulfill the needs of your business, or if you’re interested in trying something different, there are plenty of approved and endorsed analytics tools out there.

We’ve compiled a list of some of the top competitors:

Oracle Analytics Cloud

Oracle Analytics Cloud is an AI-powered solution that lets you create intuitive visualizations and share compelling stories. Unify data across multiple sources for a complete view. Leverage self-service data preparation capabilities to ingest, clean and repair data for analysis.

MicroStrategy

MicroStrategy is a data analytics platform that customizes data visualizations and builds personalized dashboards. It augments data preparation, facilitates collaboration and sends real-time alerts.

Spotfire

Spotfire is a business intelligence and data discovery platform that helps discover and analyze new data trends through dashboards. It offers advanced analytics capabilities, including predictive, geolocation and streaming analytics.

Qlik Sense

Qlik Sense is a data analytics platform that enables data-driven decisions by leveraging artificial intelligence. It allows you to create and explore intuitive visualizations with drag-and-drop capabilities.

SAS Visual Analytics

SAS Visual Analytics leverages self-service data preparation capabilities to profile, cleanse and transform data. It provides ad hoc reporting, predictive analysis and augmented analytics functions.

The Final Word on Business Intelligence and Analytics

There are plenty of choices out there. While Microsoft BI tools have a reputation for quality and reliability, an increasing number of businesses are looking towards smaller, more agile solutions. A less well-known vendor may provide a better fit for your operation.

If you decide to opt for the Microsoft Business Intelligence suite, there’s a lot to learn. These tools are dynamic, fast moving and versatile. Use them correctly, and they will become a source of great value for your company — a dependable, consistent spring of actionable information.

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