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Business intelligence process creates an environment for better decision-making. To make successful business decisions, you need to gain insight in business intelligence, follow the main steps of the key performance indicators (KPI) cycle, find the best source to store and process operational data, and assess and use standard business intelligence applications.
Business Intelligence Insights
Write A Book And Publish - PDF Free Download Write a book, elevate your profile, build a business - Upload ideas and beginner tips to get you started. The Cognos Analytics 11.0 resource guide. It seems appropriate that there’s a lot of data available when it comes to a data-related product. But, if you’re new to Cognos Analytics you might be wondering where to start. Even if you’ve used Cognos Analytics for awhile, you might wonder where the hidden gems of information are.
To help your company drive smart decisions and improve the way you do business, check out this variety of forms that can provide insight into business intelligence (BI).
Query responses: Raw data produced by the BI system, allowing the user to draw immediate conclusions
Reports: Structured and formatted data, built as part of a scheduled event, or on the fly as an ad hoc report
Derived Analysis: Insights produced by interpretation of a front-end system’s output, after that application has applied rules, heuristics, other business information, and context to it, such as in a dashboard or scorecard
Essential Steps of the Key Performance Indicators Cycle
Business intelligence (BI) is an activity, tool, or process that allows businesses to create clarity and support around their decision-making approach by determining key performance indicators (KPIs). The success level of any business endeavor can almost be measured or quantified in some aspect:
Step 1: Build or define the core business strategy or objectives
Step 2: Specify progress metrics (KPI’s), and define thresholds that indicate degrees of success.
Step 3: Measure performance over time as a baseline
Step 4: Adjust tactics and gauge correlative changes in success metrics
Step 5: Apply lessons to subsequent strategy definition
But business intelligence is very much a cultural phenomenon, moving away from gut-feel strategic choices and moving toward an evidence-driven rational approach to business.
Common Operational Data Sources in Business Intelligence
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Businesses digitally store a tremendous amount of operational data, and for business intelligence to function, it needs wide-open roads between data sources. Mainframe legacy systems still form the foundation of many companies’ data centers because of their ability to process and harbor huge quantities of data, but their data is notoriously difficult to get to as many of the legacy applications are obsolete, proprietary, or pre-standards software. Other options for data sources are:
Enterprise Resource Planning (ERP): Often implemented throughout the organization in modules that map to specific business domains, such as supply-chain, human resources, finance, accounts payable, and so on. ERP systems store a lot of transactional data used in today’s BI environments.
Customer Relationship Management: A common data source for business intelligence, CRM systems do just what they say: they process and store customer profile and behavior information, like purchase activity.
E-Commerce: Web applications can act as source data systems for business intelligence platforms by feeding real-time sales activity.
Common Business Intelligence Applications
When choosing a business intelligence application, your goal is put an effective Business Intelligence (BI) solution into place, and you’re looking at processes and software. This list represents some of the more frequently used BI applications:
Source Data
Microsoft: SQL Server, Access
Oracle: Oracle 11g
SAP: N/A
IBM: DB2
Business Objects: N/A
ETL, Data Integration, Warehousing
Microsoft: Integration Services aka SSIS (formerly known as DTS)
Oracle: Warehouse Builder
SAP: SAP BW
IBM: DB2 Data Warehouse, Warehouse ManagerWebSphere DataStage (ETL) IBM Information Server
Business Objects: Business Objects XI R2: Data Integrator (ETL) Data Federator (virtualization) Rapid Marts (standard platform data marts)
Query and Analysis
Microsoft: SQL Server Analysis Services, Access, Excel
Oracle: Warehouse Builder, Oracle Hyperion Essbase
SAP: Netweaver BI
IBM: Various
Business Objects: Business Objects XI R2: Web Intelligence (query tool) Voyager (OLAP) Desktop Intelligence (query tool)
Reporting, Information
Microsoft: SQL Server Reporting Services, Access
Oracle: BI Suite Enterprise & Standard Editions: query, analysis, reporting, Siebel Answers, Interactive Dashboards
SAP: Netweaver BI
IBM: BIRT, Design Studio, Alphablox
Business Objects: Crystal Reports
Other Front-End Tools
Microsoft: Excel Pivot Tables, PerformancePoint 2007 (enterprise scorecarding)
Oracle: Oracle Data Mining
SAP: Netweaver BI
IBM: IBM Intelligent Miner (data mining)
Business Objects: Crystal Xcelsius (visualization tools), Crystal Vision (dashboard), InfoView (BI portal)
Specialty Apps
Microsoft: MS Sharepoint Server 2007 (report distribution)
Oracle: Business domain operational analytics applications, Hyperion System 9 Financial Management, Financial Planning
SAP: ERP Software, Financial Analytics (formerly Outlooksoft)
IBM: Websphere Content Discovery (unstructured search)
Business Objects: Information OnDemand (hosted BI solutions), Performance Management (Formerly Cartesis)