Business Intelligence tools such as SAP Crystal Reports and IBM Cognos appeared in the early years to speed up decision-making processes. To transform functional data into useful data, both tools require large investments in IT infrastructure – involvement in the development of several well-experienced professionals. There are reasonable arguments for companies using traditional Business Intelligence methods, for example, greater reporting functionality. Unfortunately, the overall cost of these solutions is too high. Below you’ll find a brief explanation of the benefits of Power BI for data analysis.
New self-service Business Intelligence era
In recent years, business intelligence services operating in real-time began to appear. These tools collect data and provide live access to it. Data collected by using various systems, transaction databases, flat files, and weblogs – is integrated, updated, and stored in a data warehouse on an ongoing basis. Costs of real-time BI are falling thanks to the use of the power of the data warehouse located on the cloud.
There are more and more companies on the market specializing in business intelligence real-time solutions. Many of them offer customized pricing models. Will this, among others, cause the end of traditional BI tools? But the answer is not that simple. If a company decides that data centralization might be unprofitable, then a simpler and cheaper implementation tool will win.
If you’re ready to try the technologies of the future – I recommend starting with Power BI and Microsoft Azure.
What is Power BI?
Power BI is a set of software services, apps, and connections that work together to convert disparate data sources into consistent, visually engaging, and interactive analytics.
Your data may be in the form of an Excel spreadsheet or a collection of cloud and on-premises hybrid data storage. Power BI makes it simple to connect to data sources, visualize and uncover what’s essential, and share your findings with anyone you like. [1]
The Power BI product consists of several applications, each of which has its own features and uses. This includes the following:
Power Query: A data connection tool that allows you to modify, integrate, and improve data from many sources.
Power Pivot: A data modeling tool for creating data models
Power View: A data visualization application for creating interactive charts, graphs, maps, and other visual components.
Power Map: Another visualization tool for creating three-dimensional visual effects with the presence effect.
Power Q&A: A question and answer engine that allows you to ask basic questions about your data. [2]
Power BI for data analysis
Power BI is one of the leading tools on the market enabling data analysis. Thanks to easy operation and powerful data modeling capabilities, we can quickly implement a business data model. Additionally, we can analyze data in a multidimensional structure. Power BI uses the extensive capabilities of Direct Query, which allow the analysis of data from transaction databases in live mode. Moreover, Power BI also offers a unique transition to real-time analysis.
Microsoft Azure enables users to leverage the capabilities of Azure Stream Analytics and use this data in Power BI. That improves the application’s publication time. Stream Analytics and Power BI is an elegant combination of real-time data analysis. With these tools, the organization’s information is streamed directly from Azure Stream Analytics to analysis in Power BI.
The tools described above offer the possibility not only of fast data processing but also multiple options for publishing applications. One of the most forward-looking ways to build analytical solutions is embedded analytics. However, nesting Power BI is another function. To take full advantage of this service and share embedded dashboards and reports, you must consider the offer of Power BI Embedded or Power BI Premium services. It is an addition to the Power BI Pro account.
The integration of data through the Azure platform with the business intelligence analysis service and nesting it in the mainframe organizational system corresponds to the majority of companies that want to visually analyze data. Azure offers cloud-based data storage that increases the speed at which a company can process its internal and external data and prepare it for visualization.
Additionally, the combination of Azure and Power BI for data analysis capabilities to render interactive dashboards using REST API and SDK interfaces reduces the time to design an analytical application. Azure SQL has built-in security and advanced clusters that go far beyond the current structure of many companies. Now, thanks to this service, the company can secure its data in the cloud and expand the storage of data to the petabytes. As a result, reducing the total costs of maintaining the BI infrastructure.
Above all, data warehouses of enterprises can be complex. Different sets of data can reside on multiple servers located in different places. Thanks to the combination of SLA 98.91% Azure HDInsight and Power BI, the company can be sure that it has a BI solution that meets all system requirements and will be scalable.
Key features and benefits of Microsoft Power BI for data analysis
Include:
Very close integration with SQL Server and Azure. Using SQL Server analysis services on-premises or Azure analysis services in the cloud, users can build robust, and reusable data models. Reporting can be done by using live connection with a multidimensional database with automatic refresh enabled.
Fast Power BI implementation and lower total cost of the ownership (TCO). First report creation takes just around 1 month from zero point to production implementation. Additionally, Power BI has much lower costs compared to its competitors. It gives an opportunity for smaller companies to implement it and use it in daily reporting and data analysis.
Power BI services are available in different geographic locations. Each data center offers the same level of security, privacy, compliance, and transparency as the global version of Power BI. Additionally, apart from cloud availability, Power BI has introduced a version that can be installed on-premises. Power BI Reporting Server is a solution that gives you the possibility to connect to on-premises data sources and publish your reports and dashboards across your organization.
Wide range of different data connectors and it is still expanding. Power BI has the ability to connect to nearly any application or data source (literally hundreds of options). No matter whether those resources are located on the cloud or on-premises. A few examples include Excel spreadsheets, GitHub, Mail Chimp, SharePoint, and Google Analytics.
Version update every month. The Power BI products are being updated nearly every month with new features and functions. So, you will have access to the Microsoft resources where new features are presented and are ready to use after downloading a new version.
Other Microsoft Power BI benefits
Power BI gives you the possibility to ask questions with it’s QA feature. You can ask questions by using natural language and Power BI will prepare the answer using charts and tables. Sometimes it could be the most efficient way to perform ad-hoc analysis and get fast answers regarding your data. However, QA features are one of the most innovative features introduced into the Business Intelligence world.
You don’t need to know a programming language to start using BI for data analysis. Most parts of functionalities and analysis can be achieved by using drag and drop techniques as well as by using only the mouse and available buttons. But if your organization already uses Microsoft systems (such as Office 365), using BI for data analysis will feel natural as it integrates easily with Office 365 Groups and Microsoft Teams. Sometimes Power BI pro has some free licenses included in your Office 365 package.
Power BI is very simple to use. Almost every business user who uses excel on a daily basis will understand how to use Power BI for data analysis.
It has an easy API which can be connected to different applications. In addition, BI for data analytics services can be easily embedded into different applications – into your internal business apps such as SharePoint or SaaS applications. It allows you to share insights all around the world.
Dashboards, reports, and datasets are at the heart of Power BI. Users can create personalized dashboards that combine on-premises and cloud-born data in a single view, allowing them to monitor their most important data enterprise-wide and all their business apps.
Use cases of Power BI for data analysis
Heathrow airport
Heathrow Airport uses power BI to reduce the travelers’ stress during their trips. In addition, this airport uses BI for data analysis to visualize passenger traffic in real-time and allows workers to be prepared for changing traffic conditions. Moreover, with the implementation of power BI for data analysis, they can connect to a wide range of data sources with less effort and use that data to keep Heathrow running efficiently. [3]
Twitter
The social media company is deploying BI for data analysis with artificial intelligence to fight potentially dangerous content on its platform. For example, 95% of blocked accounts related to terrorism are identified by algorithms, not by users. Twitter’s employees and its business intelligence analysis tools track video streams in real-time and categorize them by topic. They also utilize this data to improve search possibilities and assist algorithms in identifying videos that could be of interest to users. [4]
Chipotle Mexican Grill
To track operational performance, Chipotle Mexican Grill has implemented BI for data analysis. Chipotle can now track the performance of each restaurant and show extensive information on dashboards as a result of this. Most importantly, BI data analysis tool saves the company thousands of hours. [4]
American Express
American Express uses the BI for data analysis to develop new payment service products and market offerings for customers. Moreover, using business intelligence analysis, American Express takes steps to retain customers. Power BI also helps the company in properly detecting fraud and protecting customers whose credit card data may have been stolen. [4]
To Sum Up
The above points show all benefits of Power BI for data analysis. However, the advanced implementation of Power BI and Azure still requires an experienced data science services company and a team of BI specialists. This team will integrate, clean up, load, and analyze all necessary data. Also, it is important to optimize processing efficiency in order to speed up the operational time of procedures. In the end, BI specialists will present drawn business applications using interactive dashboards.
To sum up, see how we implement embedded BI for one of the global Startups.
