BI relates to the set of technologies and techniques that collect and categorize an organization’s data and presents meaningful information in a format that helps in better decision making. The BI applications allow the developers to collect vast amounts of data from diverse sources, transform the data according to the business requirements, and present it in a visual format — tables and charts. BI does not make decisions for an enterprise but eases the analysis of data to arrive at actionable results.
With that said, let’s look at some of the important and buzzwords from the BI domain.
X Analytics: X Analytics, a term recently coined by the Gartner research firm, is the ability to run any type of analytics on all of an organization’s structured and unstructured data, no matter where or in what format that data resides.
Decision Intelligence: Decision intelligence is an engineering discipline that augments data science with theory from social science, decision theory, and managerial science. Its application provides a framework for best practices in organizational decision-making and processes for applying machine learning at scale. The basic idea is that decisions are based on our understanding of how actions lead to outcomes. Decision intelligence is a discipline for analyzing this chain of cause and effect, and decision modeling is a visual language for representing these chains.
Prescriptive Analytics: Prescriptive analytics is the third and final phase of business analytics, which also includes descriptive and predictive analytics. Referred to as the “final frontier of analytic capabilities, prescriptive analytics entails the application of mathematical and computational sciences and suggests decision options to take advantage of the results of descriptive and predictive analytics.
Self-service BI: Self-service business intelligence (BI) is an approach to data analytics that enables business users to access and explore data sets even if they don’t have a background in BI or related functions like data mining and statistical analysis.
Augmented Data Management: Augmented data management is the application of AI to enhance or automate data management tasks. It has the ability to support data talent, such as the above-mentioned data scientists, with time-consuming and data-intensive tasks which might normally be done manually.
Embedded Analytics: Embedded analytics is the technology designed to make data analysis and business intelligence more accessible by any application or user.
Collaborative BI: Collaborative business intelligence is the merging of traditional BI with collaboration tools. It enables people across the organization to see the data — in a form they can understand. This strategy helps create greater alignment within an organization and fosters the communication that’s often missing.
Real-Time Data: Real-time data is information that is delivered immediately after collection. There is no delay in the timeliness of the information provided.
Visual Business Analytics: Visual Business Intelligence (VBI) is knowledge based on the application of visual data to a business problem or opportunity. The process of visual business intelligence starts with the collection of visual data which is analyzed to create unique information. This information becomes knowledge when it is applied to a business problem or opportunity.
Smart Data: Smart data is digital information that is formatted so it can be acted upon at the collection point before being sent to a downstream analytics platform for further data consolidation and analytics. The term smart data is often associated with the Internet of Things (IoT) and the data that smart sensors embedded in physical objects produce.
Hope this was helpful.