Tuesday, July 31, 2007

Business Intelligence-Session4








To view the previous sessions
Session 1
Session 2
Session 3

BUSINESS INTELLIGENCE AND DATA WAREHOUSING MERGED

The rapid pace of today’s business environment has made Business Intelligence (BI) systems indispensable to an organization’s success. BI systems turn a company's raw data into useable information that can help management identify important trends, analyze customer behavior, and make intelligent business decisions quickly. Over the past few years, business intelligence systems have been used to understand and address back office needs such as efficiency and productivity. Now organizations are increasingly using BI to analyze customer behavior, understand market trends, and search for new opportunities.

BI relies on Data Warehousing (a data repository designed to support an organization's decision making), making cost-effective storing and managing of warehouse data critical to any BIDW solution.

Without an effective data warehouse, organizations cannot extract the data required for information analysis in time to facilitate expedient decision-making. The ability to obtain information in real-time has become increasingly critical in recent years because decision-making cycle times have been drastically reduced.
Competitive pressures require businesses to make intelligent decisions based on their incoming business data and do it quickly. Simply put, the ability to turn raw data into useful information in a timely manner can add hundreds of thousands up to millions of dollars to an organization’s bottom line.




The figure above illustrates the major components of a BI system and the process of generating business results from raw data (the operational data that is used to run the business). A brief overview of the general functions involved in the process follows.

BIDW PROCESS:













Step 1: Raw data is stored

Raw data is typically stored, retrieved, and updated by an organization’s on-line transaction processing (OLTP) system. Additional data that feeds into the data warehouse may include external and legacy data that is useful to analyze the business.

Step 2: Information is cleansed and optimized

The information is then cleansed (for example, all duplicate items are removed) and optimized for decision support applications (i.e. structured for queries and analysis vs. structured for transactions).
It is usually “read only” (meaning no updates allowed) and stored on separate systems to lessen the impact on the operational systems.

Step 3: Data mining, query and analytical tools generate intelligence

Various data mining, query and analytical tools generate the intelligence that enables
companies to spot trends, enhance business relationships, and create new opportunities.

Step 4: Organizations use intelligence to make strategic business decisions

With this intelligence, organizations can make effective decisions, and create strategies and programs for competitive advantage.

Step 5: The system is regulated by an overall corporate security policy

Information in a data warehouse is typically confidential and critical to a company's business operations.
Consequently, access to all functions and contents of a data warehouse environment must be secure from both external as well as internal threats and should be regulated by an overall, corporate security policy.

Step 6: Business performance management applications track results

A well-run BIDW operation also includes Business Performance Management (BPM)
applications, which help track the results of the decisions made and the performance of the programs created.


BIDW Drivers/Trends

The world is changing and the need for accurate and timely business intelligence is ever more pressing.

Key drivers that are making BIDW solutions mission critical include:

Rapid increase in “information democracy” i.e., business is putting BI tools and data in the hands of large numbers and types of users, not just an elite few. More people are getting more information in more detail on more devices.

Businesses are required to make more decisions, more frequently and more accurately in shorter time periods. The amount of time between when a decision is made and when feedback is received (requiring a new decision) is becoming shorter and shorter. The ability to make intelligent business decisions quickly is imperative to remain competitive.

Data is being customized on a mass scale. Personalized information such as portals, digital domains, recommendations, and news feeds are commonplace – all of these require that data warehouses be flexible enough to provide different views to different people.

New legislation and compliance regulations have made BIDW mission critical. Regulatory requirements (such as Sarbanes-Oxley, HIPAA, Gramm-Leach-Bliley, etc., and non-U.S. equivalents) put greater demands on determining and maintaining business intelligence and have made access to and analysis of information critical. Data must be captured, retained, and managed in a way that will satisfy courts and regulators.

The diversity of data is enormous. Organizations must store and manage data from multiple different sources such as ERP and CRM systems, and in a variety of formats such as text, images, voice, video, unstructured data, and more.

The increased need for better security due to wider data access availability and a larger number of users. Organizations around the world are looking for ways to reduce the risk associated with managing growing and disparate forms of data.


In addition, there are a number of industry-specific drivers .Taken all together, it’s
clear that the need for timely business intelligence has become critical in today’s business world.

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