Self-service Business Intelligence Tools: The Roadway Towards Gartner Magic Quadrant Excellence – Self-service business intelligence (BI) is an approach to data analytics that allows business users to access and explore data sets even if they have no experience in BI or related functions such as data mining and statistical analysis. Self-service BI tools allow users to filter, sort, analyze and visualize data without involving the organization’s BI and IT teams.
Organizations are implementing self-service BI capabilities to make it easier for employees, from executives to first-line workers, to gain actionable business insights from data collected in BI systems. The primary goal is to encourage informed decision-making that results in positive business results, such as increased efficiency, better customer satisfaction, and higher revenue and profits.
Self-service Business Intelligence Tools: The Roadway Towards Gartner Magic Quadrant Excellence
In addition to traditional BI tools and processes, the BI team or IT performs data analysis for business users. In this approach, users request new analytical queries, which a BI analyst or other BI professional writes and runs for them. Similarly, users request new reports and BI dashboards, typically through a request collection process initiated by BI employees.
What Is Self Service Business Intelligence (self Service Bi)?
Once the project is approved—which in some cases can take weeks—the BI team prepares the necessary data or, if necessary, works with IT to extract it from source systems, transform and clean it, and load it into a data warehouse or other data warehouse . The BI team then creates queries to produce the required analytics results and designs a dashboard or report to display the information.
On the other hand, a self-service BI environment allows business analysts, executives, and other users to run their own queries and create their own data visualizations, dashboards, and reports. Since some of these users may not be technically savvy, it is imperative that the user interface (UI) in self-service analysis software is intuitive and easy to use. But self-service BI systems should meet the needs of both casual users, who may just want to look at data, and power users with more technical skills.
Training should be provided to help self-service users understand what data is available and how it can be interrogated and used to make data-driven business decisions. In many cases, BI team members also support users as needed on an ongoing basis and promote BI best practices throughout the organization.
Self-service BI enables business users to access, model, and analyze data, which can lead to faster, more agile responses to data insights than is feasible with traditional BI.
Top 10 Key Features Of Bi Tools In 2020
The expanded data access and analytical capabilities that self-service BI provides can benefit businesses in a variety of ways. Potential benefits include:
Self-service BI implementation also presents different challenges for organizations. Barriers and barriers to a successful self-service initiative include:
To avoid or overcome such challenges, an organization must start with a well-planned BI strategy, including a solid BI architecture that establishes technology and governance standards. Those foundational elements can help ensure an organization has the right data sets and infrastructure to support the use of self-service BI tools across the enterprise.
In addition, a BI training program should educate workers not only how to use self-service systems, but also how to find the business data they need and create effective data visualizations, dashboards and reports. Meanwhile, the data governance policy should define key data quality metrics; data management, access and use policies; procedures for sharing reports and dashboards; and how data security and privacy protection will be maintained.
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Tableau, Qlik and Tibco Spotfire were among the early vendors of self-service BI and data visualization tools. Now, software vendors that once offered traditional BI tools for skilled analysts are also offering self-service ones. In fact, consulting firm Gartner characterizes the modern analytics and BI platform as a set of easy-to-use tools that support a complete data analytics workflow with an emphasis on self-service capabilities and advanced analytics features designed to help users find, prepare and analyze data.
Microsoft Power BI is another prominent self-service BI platform. Some of the many other self-service options available to customers come from IBM, Oracle, SAP and SAS, as well as vendors including AWS, Domo, Google’s Looker unit, MicroStrategy, Pyramid Analytics, Sisense, ThoughtSpot and Yellowfin . Salesforce, which acquired Tableau in 2019, also offered its own BI software, but it is now integrated into the Tableau product line. Information Builders was also a significant BI vendor before being acquired by Tibco in early 2021.
Ease of use, sophistication, and features vary for each vendor’s self-service BI tools. For example, some platforms may be used primarily for simple dashboards and visualizations rather than more complex data analysis and related tasks, such as self-service data preparation, data discovery, and interactive visual exploration.
Core features of self-service BI software include ad hoc queries, data visualization, dashboard design, and report generation capabilities. The software can be used as a relatively simple self-service reporting tool by executives and operations workers who only need to see specific information, while more advanced users can take advantage of its query and design features to share analytics results with others.
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Self-service tools also offer a variety of other features, either as standard items or as optional extras. Some of these items include:
Augmented analytics technologies are increasingly becoming key components of self-service BI platforms. They include natural language query capabilities that eliminate the need to write queries in SQL or other programming languages, as well as artificial intelligence and machine learning algorithms that can identify relevant data, explain the meaning of data elements, automate the data preparation process, and suggest appropriate types data visualization. Gartner predicts that augmented analytics features will be “ubiquitous” in BI tools by 2022.
Other notable trends include the introduction of low-code and no-code development tools by manufacturers to simplify the process of creating BI applications, plus the addition of support for multi-cloud environments to BI platforms. Overall, cloud use for BI and analytics is on the rise — in its 2021 “Magic Quadrant for Analytics and Business Intelligence Platforms” report, Gartner said the “vast majority” of new spending on BI systems is for applications in the cloud.
The Business Applications Research Center (BARC), an analyst firm that focuses primarily on BI and data management software, said that 2,865 users, consultants and vendors it surveyed in 2020 ranked self-service BI as the fifth most important BI trend. Data discovery and visualization and establishing a data-driven culture, both closely related to self-service BI, were No. 2 and No. 3, according to BARC’s “BI Trend Monitor 2020” report. Data quality and master data management were first on the list, while data governance was fourth. Do you know what problems business intelligence can solve and what BI tools can be considered good?
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Nowadays, the business intelligence market is heating up. Both the investment community and the IT circle are paying a lot of attention to big data and business intelligence. But do you know what problems BI tools can solve and what types of BI tools can be considered good?
Based on studying the Gartner Magic Quadrant evaluation criteria for analytics and business intelligence platforms, I have summarized the top 10 key features of BI tools for your reference.
Overall, as users’ data sources become more extensive, their BI preferences change. They prefer self-service development, interactive dashboards, and self-service data exploration. In all fairness, users increasingly want to do their own data analysis without having to seek support from the IT department.
Good BI tools can achieve platform security, manage platform users, monitor access and usage, optimize performance, support cross-operating systems, and ensure system high availability and disaster recovery.
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As part of enterprise informatization, there are many reasons for a BI platform to do management and disaster recovery separately. On the one hand, governments, Internet companies and large enterprises attach great importance to the construction of computerization and require special maintenance. On the other hand, BI systems have gradually become a support for business management decisions and play an increasingly important role. Businesses need a BI system to provide stable services throughout the day.
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