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Business Intelligence Putting together all of the pieces of the puzzle Business intelligence (BI) refers to all of the applications and technologies used to gather, provide access to, and analyze data and information to support decision-making efforts Chapter 5: Business Intelligence Business Intelligence vs Business Analytics • Business Intelligence – Querying, reporting, online analytical processing, business analytics • Business Analytics – A subset of BI based upon statistics, prediction and organization. • BI answers – What happened? – Where the problem is How many? How often? What actions are needed • BA answers – – – – Why is this happening? What will happen if these trends continue? What will happen next? What is the best (or worst) that can happen? Sun Tzu in The Art of War • To succeed in war, one should have full knowledge of one’s own strengths and weaknesses and full knowledge of the enemy’s strengths and weaknesses. • Lack of either one might result in defeat. Many businesses today say “how can I understand my competitor when I can’t even understand myself. That is what we are trying to solve using business intelligence. The Problem: Data Rich, Information Poor • With all of the data being captured and generated by SCM, CRM and ERP systems, as well as the other digital data being created and transmitted (spreadsheets, fields in database files, word processing documents, video clips, email and text messages, voice mail, etc.) explosion. , businesses are facing a digital • The amount of data generated is doubling every year – Some believe it will soon double monthly • Data is a strategic asset for a business, and if the asset is not used, the business is wasting resources. Having BI promotes understanding: Asking WHY? • Where has the business been? (historical perspective) • Where is the business now? (modify or encourage to continue) • Where will the business be in the future? (predict future direction) DATA MINING • The center of any business intelligence effort is data mining. – – • BI tells you what happened. Data mining tells you why it happened. Data mining: the use of advanced statistical techniques to analyze large amounts of data in order to find patterns, relationships and infer rules that might be used to predict future behavior. • • Uses query tools, multidimensional analysis, intelligent agents and various statistical tools Algorithms are applied to data sets to uncover inherent trends and patterns in the data. Data Mining Operations • Predict trends and behaviors • Identify unknown patterns • Determine how things fit together – What goes with what? • Identify patterns • Attempting to understand characteristics • The business intelligence tool used by most organizations is Microsoft Excel and its data analysis functionality, especially pivot tables. • By adding a Report Filter to a Pivot Table, you can add another dimension of information: 3-D (rows and columns and layers). – Creating a 3-dimensional Pivot Table in Excel is a means of conceptually building a data warehouse. Report Filters represent the depth layer – Slicers also let you do this (multiple values for a given field) • Pivot Tables can help you see relationships in the data