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
>>Chapter 2 : Business Intelligence Essentials <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
- Types of Business Intelligence
- Roles of Business Intelligence in Modern Business
- Role of Business Intelligence in Knowledge Management
Types of Business Intelligence
Now let us look at some of the types of BI. Types of BI include Business Modelling which describes larger picture of business problems, and solutions and information flow from source to destination. It involves models, pictures that can provide information in a graphical manner to the users of an organisation. Thus, enabling the users to communicate and understand processes and business rules in detail.
Some of the types are:
· Business process Modelling: It is an activity to represent the processes of an organisation to help in the analysis and improvement of the current process.
· Data flow Modelling: It is the process by which we can identify, model and document the movement of data around an information system. It checks processes (activities that transform data from one form to another), data stores (the areas holding data), external entity (what sends data into a system or receives data from a system), and data flows (routes through which data can flow).
· Data Modelling: In this method, the data requirements needed to support the business processes of an organisation is defined and analysed. It can be performed during various types of projects and in multiple phases of the project.
· Dimensional Modelling: According to Dr. Kimball1 Data modelling is a design technique for databases intended to support end-user queries in a data warehouse.
· ETL & Data Warehouse: As discussed earlier, data warehouse is a database that stores business related information. ETL is the tool used to extract, transform and load data into the data warehouse.
· BI Reporting: To create a successful BI report, a lot of attention must be given to both – the business end-users and IT professionals. Business users usually feel that looking at the BI report is like looking at the data warehouse itself. So, if they do not like the report, there are chances that they will not use the data warehouse also.
· Online Analytical Processing (OLAP): It is an approach to quickly answer the queries of users. It encompasses relational reporting and data mining. OLAP finds its applications in business reporting for sales, marketing, business process management, management reporting, and financial reporting and so on.
· Dashboard Software: It is one of the types of BI. As mentioned earlier, dashboard is an interactive user interface. Dashboards contain Key Performance Indicator (KPI), metrics, trends, charts, data visualisation and so on.
· Key Performance Indicator (KPI) is often identified in a business to help them drive a business towards success and is associated with a number of business activities like Customer Relationship Management (CRM), Supply Chain Analytics or any other activities within the Organisation.
The OLAP (Online Analytical Processing) Option of the Oracle Database provides a dimensional model in support of the query and analysis that are common to business intelligence and other types of analytic applications. Oracle supports the dimensional model with both Relational and Multidimensional data types.
Roles of Business Intelligence in Modern Business
The business intelligence solutions should be contemplated carefully, and the system opted for it should prove to be consistent. Even if you add new data or new systems, or bring about major changes, business intelligence systems have to steer the company to success. Steering to accomplishment is done by integrating the new data with the existing business intelligence systems. It is one of the significant elements of this intelligence solution. Creating or developing data warehouses consume time, money and energy, whereas creating the data marts are effective. However, ensure that it contains one data within the organisation. Decision making in business intelligence has always involved utilisation of different information assets, economic conditions and sources of external
information, and semi-structured sources of information. Making right decision is the necessary information or knowledge that provides foundations for effective business activities.
Some organisations that are interested to use knowledge in decision making are forced to work out procedures that enable them to transform implicit knowledge into explicit knowledge. In today’s decision making many groups of people are involved, like the stakeholders, customers, suppliers and so on.. The scope of this decision is many cases of global nature.
Business Intelligence is the primary tool to analyse and collect data information to develop a successful business. Today businesses largely relay on the information available and can be communicated through various sources, both internally and externally with the help of Internet.
There are three types of decisions that most business organisations take. They are:
· Strategic decision: Strategic decisions are the highest level where the
decision concerns long term goal, philosophies and values of an organisation. These decisions are concerned with the entire environment in which an organisation operates. The resources, the people who form the company and the interface between them are considered. They are long term decisions.
· Tactical decision: Tactical decisions basically support the strategic decisions. They are at a middle level and are of medium importance and moderate consequences.
· Operational decision: Operational decisions are short term decisions
needed when physical assets of an organisation are acquired. These plans involve material, plant facility, and in-house capability of company personnel. Operational decisions help to understand some basic cost- volume relationship related to the operations of the company.
Role of Business Intelligence in Knowledge Management
The role of information and knowledge as a basis for competition is constantly rising the recent trend is towards the use of business performance management (BPM) applications that put these measurements into a business context. This Process oriented knowledge has been tested and is successful in several projects at IBM and federal systems. Their experience in refining the information was an important factor for a recent award as a principle contractor in the STARS (Software Technology for Adaptable and Reliable Systems).
Continuous refinement of information resources includes domain knowledge and analysis as a process by which the information used in developing software systems are identified, captured and organised with the purpose of making it reusable when creating new BI systems. One of the objectives of continuous refinement is to make all the information readily available, while making a reusability decision.
This process of refinement of information has three basic steps that recur and repeatedly for different kinds of components. They are:
1. Identification of reusable entities.
2. Abstract or Generalisation.
3. Classification and Directory for future reuse.
Challenges of BI
The advantages of using BI are many. However, few organisations face challenges when deploying business intelligence in modern business.
Some of the challenges faced by the organisations while deploying BI are:
Process: BI looks for authoritative sources of data that define limited, concrete, dimensional definitions of the business and use those to perform reporting. The challenge is in getting multiple departments on the same page. This integration would provide a single source for sustainability data plans, targets and best practices, where every individual can analyse the data. BI team members can perform all roles that helps maintain BI sustainability.
Technological: Tools for developing analytical reporting can be expensive and requires an in depth knowledge to use it effectively. Individuals require data architects, data modellers, OLAP developers, and report writers. These tools are not available to learn outside as it built for a particular process.
People: Getting the right people involved in a project, is key to success setting the right expectations and communicating well to avoid disappointment by the customer.
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