Self-service business intelligence users must fully understand the context of the data collected, and incorrect assumptions can derail decision-making success. Collaborative BI combines BI applications with collaboration tools to reduce potential misunderstandings.
Traditional BI is a technology-driven process for analyzing data and presenting insights to business users clearly and concisely. Before BI platforms became commonplace, data scientists, data statisticians and other highly technical data professionals oversaw data analysis. Translating insights and making them digestible for non-data professionals is difficult, but BI aimed to solve that problem by automatically visualizing data in easy-to-understand formats, such as graphics and dashboards.
However, only certain business users received BI reports, most often executives or those in other high-level positions. BI tools' evolution into self-service modules has helped democratize data analytics, allowing many more users -- regardless of technical skill -- to access data and create BI reports and data visualizations on their own. The result is better-informed, data-driven decision-making.
Enter: Collaborative BI
One of the emerging trends driving the growth of the BI market is collaborative BI, also known as social BI. The technology offers new advantages to traditional tools for organizations looking to gain a competitive edge.
The combination of BI and collaboration tools enables users to work together, synchronously or asynchronously within a dedicated collaboration platform. Users can discuss data reports in real time or leave comments for another user to address later. It makes it easier to ask questions and get clarification about the context of data reports without having to switch between applications. It also simplifies sharing knowledge across the organization.
In practice, collaborative BI can take the form of BI platforms that have their own collaborative tools or within existing collaboration/communication tools, such as Slack, Microsoft Teams or even social media applications. Users can receive and discuss BI reports in their usual chat spaces.
Benefits of collaborative business intelligence
Collaboration is at the heart of business success, and combining it with BI provides key benefits for organizations of all sizes:
Improve the decision-making process
Every business stores vast amounts of data, but that data is only as valuable as the insights extracted from it and how far they can travel. An employee can use a variety of data sources for analysis and produce easily digestible reports and visualizations in a collaborative BI platform. Integrated communication features quickly share the insights across the organization.
Even if a user is not technically savvy, collaborative BI tools make it easy to read reports, run data analyses and ask questions, which leads to more confident decisions.
Increasing knowledge access can break down departmental silos, opening information to all teams and individuals. Each employee can make more informed and better-aligned business decisions when everyone works off the same foundation.
The ability to ask experts questions about reports can also ensure no loss of context. Communication history is accessible to future users, which reduces the risk of misinterpretation.
Empower employees through data
The self-service capabilities of collaborative business intelligence help democratize data access and foster a data culture. In practice, it means users can do everything from generating reports to adding and manipulating their own data. Even if a user is not technically savvy, collaborative BI tools make it easy to read reports, run data analyses and ask questions, which leads to more confident decisions.
The ability to access data, as well as receive, generate and share reports on their own, helps employees feel empowered. According to a ThoughtSpot and Harvard Business Reviewsurvey, 72% of leaders said data empowerment increased employee productivity, 67% said it boosted the quality of products and services, and 69% believed it would increase employee engagement and satisfaction.
When employees can see how their data-driven input affects a project and organizational goals, they feel more involved and autonomous.
Optimize data quality and efficiency
Clean, organized and timely data is the key to optimizing data quality. When all users input and pull data from the same place, it improves data organization and efficiency. Instead of switching to different apps or documents, users can upload data through the communication tools they're already using. The database can refresh in real time, which helps eliminate redundancies and keep data up to date at scale.
A centralized BI tool can also keep workflows lean and make asset libraries searchable. Keeping data organized helps users find exactly what they're looking for, from past conversations about data to any previously shared or generated report.
Enhance data security
One centralized repository of data can simplify data governance and security. Connecting a collaborative BI tool to all data sources can help centralize all data in one platform. It's easier to track where data is coming from and identify points of risk.
Many platforms allow data teams to create approved user lists and criteria for accessing highly sensitive data or data that requires restricted access. Creating detailed permissions can help the security team ensure only approved users can access, share and discuss specific data.
Collaborative BI platform examples
Harnessing the benefits of collaborative BI depends on an organization identifying which platform is compatible and fully integrates with its current communication and collaboration tools. Several vendors lead collaborative business intelligence development.
Below is an unranked, alphabetical list of vendors that best align with the characteristics of collaborative BI, based on market research from reputable sources including Forrester and Gartner, plus additional research by TechTarget editors.
IBM Cognos
IBM Cognos Analytics is compatible with many data sources, including SQL databases, Google BigQuery and Amazon. Users can drag and drop data to create visualizations and easily share reports using email or Slack, enabling quick conversations about assets and insights. Cognos also has a mobile app, so users can get alerts from their phones and view multipage reports on the go.
Power BI
Microsoft's Power BI platform can connect to Azure and 365 apps, including Teams, Excel, PowerPoint and Outlook. Its interoperability enables users to pull insights into the apps they're most familiar with, i.e., the ones they likely use every day. Reports embedded in the apps simplify sharing and remove concerns about exporting to compatible applications.
Qlik Analytics
Qlik Analytics is particularly well-suited for users of varying skill levels. Its simple aesthetic and design make it easy for business users to understand and share insights at scale. The platform features intelligent alerts triggered by certain actions or insights related to certain roles. Users can share content with customers who don't have an account. Qlik Analytics is compatible with many social media websites, collaboration tools and databases.
Tableau
Salesforce's Tableau features a variety of in-app collaboration features, including tagging and commenting. Users can add images to their comments to provide the history and context of a visualization. The features work across desktop and mobile, empowering users to share dashboards with one another at any time. Stakeholders can set user permissions and roles.
Yellowfin
Yellowfin enables report and dashboard sharing through export, email or link to BI content. The Yellowfin app works across devices, so users can access analysis and commentary anywhere. It also has a feature called Timeline that functions like a social media feed, making it easy to follow, share, interact and collaborate with BI content in real time.
Jacob Roundy is a freelance writer and editor, specializing in a variety of technology topics, including data centers and sustainability.
