Business Intelligence

Analytics and BI Platforms

Gartner claims "Today’s analytics and BI platforms are augmented throughout and enable users to compose low/no-code workflows and applications. Cloud ecosystems and alignment with digital workplace tools are key selection factors. This research helps data and analytics leaders plan for and select these platforms." 

Analytics and business intelligence (ABI) platforms allow less technical users to model, cleanse, analyze, explore, and manage data, which means they can collaborate and share findings with others. Data becomes more useful throughout an organization. Today’s ABI platforms emphasize visual self-service, are augmented by AI, and provide automated insights.

ABI platforms are adding interaction methods, like natural language query (NLQ), Natural Language Generation (NLG), or conversational analytics interfaces, like Qlik's Insight Bot, all while democratizing access to a company's data to help make decisions in today's complex business environments.

Actionable Insight

Business Intelligence refers to the processes and technologies leveraged by enterprises to collect, integrate, analyze and present pertinent business information in a format that is easy to interpret. It provides historical, current and predictive views of the business operations and turns raw data into actionable insights. Business Intelligence tools analyze data sets and present its findings using reports, summaries, dashboards, graphs, charts and maps to provide users with detailed intelligence about the state of the business.

At its core, BI is a tool that transforms data into actionable insight by using it to tell a story. Data-driven storytelling is a powerful force as it takes stats and metrics and puts them into context through a narrative that everyone inside or outside of an organization can grasp.

Data Storytelling

By asking what kind of story you want to tell with your data and what message you want to convey to your audience, designers will be able to choose the right data visualization tools for their project or initiative.

Data Visualization

Understanding who your audience is will also help designers choose the right data visualization type. Designers should always put themselves in the user’s position. You may be aiming your data visualization efforts at a particular team within your organization, or you may be trying to communicate a set of trends or predictive insights to the risk management department. Designers should take the time to research their audience so that they can make a more informed decision on which data visualization chart types will make the most tangible connection with the users.