What is it (Business Intelligence)
Business intelligence (BI) is a broad category of application programs and technologies for gathering,storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications support the activities of decision support, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and data mining. BI includes a set of concepts and methods to improve business decision making by using fact-based support systems.
Business intelligence (BI) is about creating value for our organizations based on data or, more precisely, facts. While it seems like another buzzword to describe what successful entrepreneurs have been doing for years, if not centuries, that is, using business common sense. From a modern business-value perspective,corporations use BI to enhance decision-making capabilities for managerial processes (e.g., planning,
budgeting, controlling, assessing, measuring, and monitoring) and to ensure critical information is exploited in a timely manner. And computer systems are the tools that help us do that better, faster, and with more reliability.
Defining BI
Business Intelligence is the art of gaining a business advantage from data by answering fundamental questions, such as how various customers rank, how business is doing now and if continued the current path, what clinical trials should be continued and which should stop having money dumped into! With a strong BI, companies can support decisions with more than just a gut feeling. Creating a fact-based “decisioning” framework via a strong computer system provides confidence in any decisions made.
Business intelligence is not necessarily about tools and technologies; rather it is a strategy of combining data from various sources with methodologies that make those facts solidify in a cohesive manner.The data part of this strategy is data warehousing Once the data is sourced, scrubbed,enriched, conformed, and finally housed in “access-ready” formats BI tools can make the data sing and dance.
Traditional BI makes use of past data points (what you know about the data from a historical perspective)and displays it for the end user to make important inferences. The historical reporting takes advantage of the dimensionality in the data to “slice and dice” by reporting facts along any number of dimensions.Early reporting tools allowed programmers to define exactly what they wanted to present in varying levels of
granularity and aggregation. In the 1980’s a plethora of OLAP style data structures emerged, which included MOLAP, ROLAP and Hybrid-ROLAP. All of which provided the ability to drill in, around and through to make sense of the data presented.
While OLAP is certainly not dead, highly structured interfaces to the data came out of an organization’s executive branch interested in the details. In other words, taking data from “green bar” and simply transferring it to the “browser” was not enough.
Management needed to synthesize the data into meaningful bits of information. “Tell me what’s wrong.Highlight the facts for me,” was the driving force behind the dashboard and scorecards in today’s electronic toolbox.
Reporting on the past can only show what has happened, not what the future may bring. Past information must be combined with some real-time information and then layered with analytics in order to have true foreknowledge. This is where data mining, forecasting and other predictive analytics play an important role.This also turns out to be a major differentiator for SAS relative to its competitors.
SAS and BI
Having just celebrated 30 years of providing software for decision support, it is safe to say SAS has always done BI. From the early days of helping agricultural universities share statistical algorithms to supporting Fortune 100 companies today, SAS solutions take data and make sense of the patterns and provide flexibility and power in how to display and share information.
In SAS software, Business Intelligence includes:
• A set of client applications designed for a specific type of business or analyst
• SAS server processes designed to provide specific types of services for the client applications
• A centralized metadata management facility
Future of BI—Business Intelligence 2.0
As it relates to
modern computing, the concepts behind BI have been in use for decades. One of the paradigm shifts noted in recent years is moving beyond simple reporting to proactive analysis of the data and providing prescriptive recommendations on how to interpret the data. This, of course, relies on the fact that corporations can successfully move from caring about what happened in the past to a desire to not only know
what’s wrong but what is likely to get worse if nothing is done. That is where the power of advanced analytics plays such a powerful role. What lies ahead if the leap can be made that tools like reporting, querying, OLAP, dashboards, scorecards and portals can be successfully used to help make sense of the world around us?
Wikipedia defines BI like this:
… a business management term which refers to applications and technologies… used to gather, provide access to, and analyze data and information about…company operations. Businessintelligence systems… help companies have a more comprehensive knowledge of the factorsaffecting their business, such as metrics on sales, production, [and] internal operations…[BI systems] can help companies… make better business decisions. (Source: Wikipedia, 2007)
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