Companies have to answer key questions every day:
- What impact do price changes have on buying behaviour?
- Is the supply chain aligned with consumer demand?
Though companies have the data that could answer these questions few properly leverage all of their resources.
A company needs to first extract tangible information and then to make sure it gets into the right hands.
To effectively and efficiently run the business a company must convert their data into knowledge.
How Business Intelligence is defined varies a great deal from business to business. This is because the organizational structure, products and channels are unique for each business.
Regardless, most Business Intelligence solutions utilize a set of key components below and tying it all together in an integrated architecture:
- Database management. This includes the linked disciplines of analyzing, designing, deploying, and managing;
- Data extraction, transformation, and loading (ETL). ETL offers facilities to ease the burden of populating diverse Business Intelligence data stores, both initially and incrementally;
- Query, reporting, and analysis. This includes software for building database schemas and tools honed to facilitate getting answers to a variety of business questions;
- Repositories. These are responsible for holding meta-data and other information assets and preparing them for reuse;
- Integrated Architecture. The process of integrating, monitoring, and controlling a variety of systems and processes requires an architecture which considers the entire environment including OLTP systems, supplier /customer dependencies and overall information flow and utilization.
Indeed, for many companies, making better decisions faster can make the difference between surviving and thriving in an increasingly competitive marketplace. Knowing the best way to facilitate customer retention, improve product design, optimize distribution channels, or target markets more directly, for example, can all have an immediate impact on the bottom line. META Group believes that to realize these benefits you need to approach data warehousing and Business Intelligence with the entire business in mind. This means that when you define your models for data, use, and deployment, you need to focus on the business process, performance metrics, and business objectives that drive the business.
Business intelligence is a broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications include the activities of decision support systems, query and reporting, Online Analytical Processing (OLAP), statistical analysis, forecasting, and data mining. Business intelligence applications can be:
- Mission-critical and integral to an enterprise's operations or occasional to meet a special requirement;
- Enterprise-wide or local to one division, department, or project;
- Centrally initiated or driven by user demand.