The business intelligence platform revolution
The business intelligence landscape has undergone significant transformation in the last few years, largely due to advancements in technology and changes in business needs. The BI landscape has transformed from being a tool primarily for data analysts to a platform accessible to a wider range of users with more advanced capabilities, features, and integration options.
“Business intelligence is no longer just for the data analysts. Modern BI platforms enable users at all levels of an organization to access and analyze data in real-time, empowering them to make more informed decisions and take action based on insights derived from data.”
Howard Dresner, Research Consultant
The business intelligence (BI) landscape has undergone significant transformation in the last few years, largely due to advancements in technology and changes in business needs. The BI landscape has evolved from being a tool primarily for data analysts to platforms designed for a wider range of users. In 2018, Gartner recognized the BI environment was radically evolving and had the potential to bring about massive transformations across industries. Gartner renamed its Magic Quadrant for BI “Analytics and Business Intelligence platforms.”
Today, BI platforms are designed to provide users with self-service analytics capabilities, allowing them to easily access and analyze data without the need for extensive technical knowledge. These platforms also often include features such as machine learning and natural language processing, which further enhance their capabilities and enable more advanced analysis.
Below shows the venn diagram that depicts the role that business intelligence plays between your business, the management team, and the IT department.
The point being made, is that BI is not just for CEO dashboards. It’s meant to serve the needs of all 3 groups, and often times it will expand even further beyond these audiences.
Gartner believes data visualization has now been commoditized and all BI vendors can build interactive KPI dashboards with common chart forms while drawing on a wide range of data sources. Augmented analytics is the differentiator to help businesses use their data more effectively than manually.
Features that decide the winners and losers
Analytics and Business Intelligence (BI) platforms should include a range of features to effectively support data-driven decision-making. Here are some key features that differentiate the most amazing and red hot platforms from mediocre / declining ones:
- Data integration and connectivity
- Data visualizations (pretty pictures)
- Data modeling (having the right tools)
- Data exploration and discovery
- Reporting and dashboards
- Collaboration and sharing
- Security and governance
Each of these is expanded upon below.
Data integration and connectivity
A good analytics and BI platform should be able to access a wide range of data sources, including databases, data warehouses, cloud storage, and third-party applications.
Data visualization tools help users understand and analyze data easily. A platform should include a range of visualizations, such as charts, graphs, and tables, as well as the ability to customize visualizations based on user requirements. There are so many BI software applications out there, and yet, these leading business intelligence visualization software products seem to dominate: Tableau, Microsoft Power BI, QlikView, SAP Lumira, and IBM Cognos Analytics.
Data and database modeling is usually a part of the construction of a software application. The app requires a database, so the developers create one. If you’re lucky, they design it well, and break it out to 3rd normal form, or anything close to it.
A well-stocked IT department should not shy away from data modeling, and should pay for licenses of data modeling software tools to help database professionals and solution architects to organize and structure their data for analysis, even if it is not a part of a new software application. And there’s no shortage of tools out there. Most of the leaders in this software space are well known: ER/Studio Data Architect, Toad Data Modeler, Oracle SQL Developer Data Modeler, IBM InfoSphere Data Architect, and SAP PowerDesigner.
Data exploration and discovery
The platform should include tools to enable users to explore data and discover new insights. This may include features such as data mining, machine learning, and natural language processing.
Reporting and dashboards
The platform should enable users to create reports and dashboards to summarize data and highlight key insights. These reports and dashboards should be customizable and shareable with other users.
Collaboration and sharing
Analytics and BI platforms should enable collaboration among users, allowing them to share insights and work together on data analysis. While at first this may sound like common sense, it is not always possible. Licensing is always the first culprit to this issue. “You want to see that dashboard? It’s gonna cost you more licenses.” So be cognizant of the licensing implications with eyes wide open when you select your BI platform.
Security and governance
The platform should have strong security and governance features to ensure that data is kept secure and compliant with relevant regulations.
The BI landscape has transformed
There are a handful of ways that BI has evolved transformed over the last decade or so. Each is explained below.
The emergence of cloud-based BI
Cloud-based BI platforms have become more prevalent, enabling organizations to store and access data in the cloud and allowing for greater scalability and flexibility. Many BI vendors have turned to the Software as a Service (SaaS) cloud-based model, says Sandra Durcevic in her article, Top 10 Analytics And Business Intelligence Trends For 2021. This adds flexibility, faster access to the data, better modeling capabilities, and mobile access anywhere claims Durcevic. Technologies “that enable data movement and access from multiple places will continue to rise as one of the most important business intelligence trends in 2021,” says Durcevic.
The rise of self-service BI
Self-service BI has become increasingly popular, allowing non-technical users to analyze data and create reports and visualizations without relying on IT or data analysts.
Increased adoption of artificial intelligence (AI) and machine learning (ML)
AI and ML are being integrated into BI platforms, allowing for more advanced data analysis and insights. In her article Top 10 Analytics And Business Intelligence Trends For 2021, Sandra Durcevic sees AI as another feature that will take BI tools to the next level. AI will fully analyze a dataset automatically without any effort needed by the user. “Simply choose the data source you want to analyze and the column/variable (for instance, revenue) that the algorithm should focus on,” then, calculations will be run and users will get growth/trends/forecast, value driver, key segments correlations, anomalies, and what-if analysis, says Durcevic. This should save considerable time and provide business users with access to high-quality insights while giving them a better understanding of the information they receive, even if they aren’t skilled coders. The ‘Citizen data scientist’ is a term being bandied about by many software vendors to describe BI and data integration tools that are simple enough to use and limited or no coding skills are required to make them work.
Greater focus on data governance and security
With increased concern over data privacy and security, BI platforms are placing a greater emphasis on data governance and security features to ensure the protection of sensitive data.
Integration with other technologies
BI is increasingly being integrated with other technologies, such as big data and IoT, to provide more comprehensive insights into business operations.
The prevalence of real-time data
According to Durcevic, real-time has evolved considerably over the past year and the technology should continue to grow throughout 2021. The pandemic showed the need for real-time, Durcevic believes, as rapid and accurate updates were critical in developing proper strategies when businesses had to respond quickly to highly unfortunate events.
Real-time access to data, whether it’s social media, mobile banking, instant messaging, or chatbotting, has become a norm in everyday life. “Creating ad hoc analysis has enabled businesses to stay on top of changes and adapt to immense challenges that this year has brought,” says Durcevic. Implementing live dashboards are a lot more complicated than pulling information from an in-memory database and surfacing that data into a dashboard, but giving companies access to immediate and relevant information about the business can make the data considerably more valuable, especially when dealing with customer data, contends Durcevic. Real-time data is much more valuable than ever before and this is one area where being left behind means one might never be able to catch up again.
Collaborative BI “is a combination of collaboration tools, including social media and other 2.0 technologies, with online synchronous and asynchronous tools” says Durcevic. The BI tools in Gartner's Magic Quadrant make it easier to generate automated reports that can be scheduled at specific times and shared with designated people. For example, collaborative BI tools enable users to set up business intelligence alerts, share public or embedded dashboards, as well as can track the progress of meetings, calls, e-mail exchanges, and ideas collection, says Durcevic.
BI platform winners
The Gartner 2021 Magic Quadrant for Business Intelligence (BI) is a report that provides an overview of the leading BI platforms in the market. The report evaluates vendors based on their ability to execute and completeness of vision. According to the report, the following vendors are named as leaders in the BI market:
Microsoft’s Power BI has made deep inroads in the BI space since it arrived a few years ago, mostly due to its attractive product, massive user base, and killer pricing. Microsoft offers a range of BI tools, including Power BI and Excel. These tools provide users with interactive visualizations, real-time data insights, and collaboration features along with data preparation, visual-based data discovery, interactive dashboards, and augmented analytics. It is available as a SaaS option running in the Azure cloud or as an on-premises option in Power BI Report Server.
Tableau (a Salesforce company)
A Leader in this Magic Quadrant, Tableau was recently purchased by Salesforce and it has enhanced its data preparation and data management capabilities in 2020. Tableau is a data visualization tool that provides users with a range of interactive dashboards. It offers a visual-based exploration experience that enables business users to access, prepare, analyze, and present findings derived from their data. Salesforce recently integrated its Einstein Analytics into the product, renamed it Tableau CRM, and then added powerful marketing capabilities to it. For data preparation, Tableau “released enhanced data modeling capabilities, which makes it easier to analyze data across multiple tables at different levels of detail by building relationships between tables with a simple in-browser visual experience,” says Gartner.
Qlik offers a range of BI tools, including QlikView and Qlik Sense. These tools provide users with a range of data visualization and analytics features, as well as collaboration and reporting capabilities. Qlik continues as a Leader in the 2021 Quadrant, with a strong product vision for AI- and ML-driven augmentation. Qlik’s longstanding Associative Engine adds a Cognitive Engine with AI/ML-driven functionality to Qlik Sense and offers context-aware insight suggestions and augmentation of analysis. Qlik is another vendor offering deployment flexibility, with both enterprise on-site and cloud hosting, which is cloud-provider agnostic.
Other than the leaders, a handful of other players are recognized for their innovation and ability to provide users with advanced analytics capabilities
A Niche Player in the 2021 Magic Quadrant, Amazon’s QuickSight “is a fully managed, cloud-based ABI service for performing ad hoc analysis and publishing interactive dashboards.” The platform ingests data from a variety of on-premises and cloud-based data sources into its parallel, in-memory calculation engine, SPICE, and AWS claims it can scale to hundreds of thousands of users without any server setup or management.
Domo is a Challenger in this year’s Quadrant. It is also a cloud-based ABI platform that is garnering interest because of its ease of use and fast deployment time. It offers “over 1,000 data connectors, consumer-friendly data visualizations and dashboards, and a low/no-code environment for BI application development.”
Oracle, a Visionary in this year’s Quadrant, offers the Oracle Analytics Cloud, an end-to-end cloud-first platform providing data ingestion, preparation, visualization, and mobility. Oracle has enhanced its augmented capabilities and now allows third-party components on its platform, including integration with third-party ML systems.
Another Visionary in the 2021 Magic Quadrant, SAS’s position reflects its robust and innovative product, specifically with its SAS Visual Analytics on its cloud-ready and microservices-based platform. This is an end-to-end visual and augmented data preparation, ABI, data science, ML, and AI solution. SAS’s 2020 product includes a service that provides the user with suggestions for good visual design, more optimized performance, and accessibility practices for any dashboard the user is thinking about creating. SAS Conversation Designer also lets users build customized chatbots through a low/no-code visual interface.
TIBCO Software is another Visionary, and its Spotfire “A(X) Experience represents an augmented, focused approach that enables Spotfire users to use data science techniques, geoanalytics and real-time streaming analysis in easily consumable forms, such as NLQ, NLG and automatically suggested visualizations,” says Gartner. TIBCO offers a range of BI tools, including TIBCO Spotfire and TIBCO Jaspersoft. These tools provide users with a range of data visualization and analytics features, as well as collaboration and reporting capabilities. TIBCO has improved its support for Python data functions and it handles streaming data sources directly within the application. Its new Mods developmental framework enables the rapid creation of lightweight add-ins, simplifying mashups and interactive visualizations.
A look ahead
Gartner sees a reckoning between two different platforms - the ABI and the data science and ML platform - coming up in the not-too-distant future. On the one hand, ABI platforms perform augmented data science and ML tasks, “with predictive models being executed ‘behind the scenes,’ and insights ‘surfaced’ within the ABI process flow.” On the other hand, data science and ML platforms increasingly “feature enhanced data transformation and discovery capabilities, such as data visualization, that are traditionally more characteristic of ABI platforms.” Currently, the two platforms attract different buyers, but how long that continues remains to be seen. In the meantime, the power of these platforms puts to shame the tools that were available just a few short years ago. In some ways, there’s been a harmonic convergence of tools and their capabilities, with many of these ABI tools differentiating little from each other. And that might not be such a bad thing because then, as it always should, creativity will win out.
Leading BI platforms are focused on providing users with advanced analytics capabilities, self-service data preparation, and collaboration features. The market is shifting towards cloud-based BI platforms, as organizations increasingly look to leverage the scalability and flexibility of the cloud.
- The business intelligence (BI) landscape has undergone significant changes in recent years.
- Advancements in technology, changes in business needs, and a growing demand for data-driven decision-making are driving this transformation.
- BI platforms have evolved from being tools primarily for data analysts to platforms designed for a wider range of users.
- Today's BI platforms provide users with self-service analytics capabilities, enabling them to easily access and analyze data without the need for extensive technical knowledge.
- Modern BI platforms also often include features such as machine learning and natural language processing, which further enhance their capabilities and enable more advanced analysis.