Hi Geeks,
This post is part of Series Business Intelligence – Tools & Theory
Currently running topic for this series is listed as below :
Series Business Intelligence – Tools & Theory
>>Chapter 1 : Business Intelligence an Introduction <You are here>
Continuing from my previous post on this series, If you have missed any link please visit link below
We are going to Cover the Following Points in this article
- BI Segments
- Defining Business Intelligence Value Chain
- Difference between Information and Intelligence
BI Segments
In the previous section we learnt about the history and evolution of BI. Now let us study about the segments in BI.
The most important segments or areas that Business Intelligence (BI)
covers are:
· Data warehousing (DW) (architecture, modelling, managing, processing).
· ETL processing and data integration.
· CPM, Forecasting & Reporting.
· Reporting, Information visualisation and Dashboards.
· Online Analytical Processing (OLAP) and multidimensional analysis5.
· Data cleansing and data quality management.
· Performance management.
· Data mining, statistical analysis, forecasting.
· Management Information Systems (MIS).
It is necessary for organisations to assess how they can use BI and information to improve results and to use structured approaches to ensure that its investments in BI deliver business value.
Many companies these days seek to use strategies that differentiate customers based on their significance. In retail banking, a customer with loans, large savings account, a checking account with large balances, credit card balances and who uses on-line banking is much more valuable than a customer with only a low-balance checking account who comes into a branch frequently. Bank would want to retain the former customer, whereas it might be willing to lose the latter.
The Business value of BI lies in its use within organisation processes that impact working process that constrain profits or reduce costs, and/or in its use within those working process itself.
Business values also have management processes and operational processes that take into account about the differences in customer value and treat the highly valuable customers preferentially. For example, a bank may ignore a late fee on a loan payment for the valuable customer, but not for the less valuable customer.
John Hagerty6, vice-president an analyst at firm AMR Research.
He defines the business intelligence tools used by the finance department
(all of which are sold as part of CPM platforms) as:
· Planning, budgeting and forecasting: contribution, aggregation, manipulation, and approval of the financial plan on a periodic or continual basis.
· Financial consolidations and reporting: legal and statutory consolidation systems, along with more comprehensive financial statement generation capabilities.
· Financial analytics and dashboards: profitability applications, role- specific dashboards, metrics, and specific financial analytics for detailed financial processes.
· Financial governance, risk management, and compliance: governance and control requirements that include national and international regulations, Example: Sarbanes-Oxley or the International Financial Reporting Standards.
· Scorecards and strategy: Methodology-based scorecards, such as the Balanced Scorecard, and strategy management applications.
Defining Business Intelligence Value Chain
Business intelligence involves the combination of core data with correct contextual information. It detects significant events and clarifies issues to examine business trends, to develop and adapt quickly to conditions and to make intelligent business decisions on uncertain judgements and contradictory information. It depends on investigation and analysis of unrelated data, to provide relevant insights, identify trends and discover opportunities.
Example Many public-private sector implements BI value chain. In the organisation. Ideally, any manager or knowledge analyst is able to create data requests without programmer assistance and accomplishes answers at the speed of thought. Queries should be immediately asked and answered in order to maintain the thought flow on a particular topic.
In the next section we will learn about BI value chain.
Business Intelligence value chain
Data resource is the initial stage in BI value chain where data is developed from a data resource. In order to sustain the knowledge environment of an intelligent knowledge organisation, data is used as the raw material for information and in turn information is used as a raw material for knowledge environment. Further, knowledge is the raw material for business intelligence which supports business strategies. As shown figure 1.2, BI is involved in:
Value chain
Data: It is a raw fact that do not have context; it is meaningless and is difficult to understand. Facts are figures, characters, character strings, content, images, voice, video and any other form. „Data in context‟ is data that have meaning and can be understood easily. It is not yet information because it has no significance or time frame.
Information: It is a set of data that is relevant to one or more people in time or for a period of time. Information is data with meaning, significance and reason. A set of data in context becomes information when one or more people are ready to accept that message according to their needs. A message without meaning, significance or reason is simply noise.
Knowledge: It is an awareness of the fact or condition, to know something with knowledge gained through experience or involvement. It is the associated with knowing truth or fact. „Tacit knowledge‟ is the knowledge that is in people’s head. It makes people smart and they act intelligently. „Explicit knowledge‟ is the knowledge that has been delivered clearly to a community of people, such as an organisation.
Organisational knowledge: It is information that is significant to an organisation, It is combined with experience and understanding. It is analysis, indication and mixture about what information means to the business and its advantages. It is the ability to learn, be aware of and deal with new situations; to apply knowledge and think theoretically. It is the core of an intelligent learning organisation that must be accumulated, grown and managed. This knowledge is a rational understanding of information that leads to business intelligence.
Difference between Information and Intelligence
In the previous unit we learnt about the history and evolution of BI, now let us study the difference between information and intelligence and also the way these are implemented in day to day businesses. We use these terms very often interchangeably, but let us look at the differences in both these terms as given below:
Differences between Information and Intelligence
|
INFORMATION |
INTELLIGENCE |
|
Raw Data |
Derived from Latin verb, john-enmark meaning “to understand,” or “to choose between”. |
|
Verified to be Precise |
Referred as the „intelligence cycle‟ |
|
Timely |
Logical rational process |
|
Presented within Context |
Gain Knowledge |
|
Effective understanding and decrease in uncertainty |
Identify its importance and link with other data. |
|
Effective understanding and decrease in uncertainty |
Develop a plan for action. |
|
Use the plan to accomplish a desired goal. |
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