Intro to BI

Intro to BI

1. BI Systems

   • BI Systems useful as they are enhanced with additional visualisation, alerts, and performance measurement compatibility. BI systems take in information such as change in product price, change in advertising mediums, change in customer spending power etc, and put it into the database. BI system will then generate ins such as "what was the % increase in sales after the TV ad published on the same month?", or "does the increase in cost spending power resulting them in supporting a higher priced product?"

2. Business Intelligence

   • BI is a computerised support for organisation's operations. It is the evolution of decision support. It's objective is to 1. facilite closing the gap between biz's current performance vs their desired performance, 2. transforms data into information/knowledge > into decisions > into actions, 3. BI provides easy access to data & models to biz mgmt so that they can conduct analysis.

3. Business Pressures

   • Environmental pressures like diff market conditions, diff customer demands, globalisation etc pressures businesses to come up w new strategy, source new collaborations and increase in productivity. With the help of BI and integrated computerised decision support, business can make better analysis, predictions and decisions to combat these business pressures. (Business Pressures-Response-Support Model)

4. BI Architecture (4 Major Components)

   • 1. Data Warehouse: (Stores, organises, standardise data). Data in data warehouse used to include historical data, but now, some DW includes access to current data so they can provide real time decision support. Data warehouse stores historical data (up to 10 years) (as data WH involves data mining thus need more data) and is takes in data on an interim basis, whereas database stores only up to 3 years and data is updated almost immediately. *Chap 2
   • 2. Business analytics: Collection of tools for mining and manipulating of data in data warehouse, thus generating analysis results)
   • 3. Business Performance Mgmt (BPM)/Corporate Performance Mgmt (CPM): Monitors & analyses performance with applications and tools to better manage their operations *Chap 3
   • 4. User Interface: BI provides a more comprehensive graphical/pictorial view of corporate performance measures, trends and exceptions. Eg: Dashboard, browser, portal etc

5. Intelligence

   • Steps involved in creation of intelligence: 1. Data WH deployment 2. Creation of intelligence 3. BI Governance - which to prioritise? partnership between functional area of heads or partnerships between customers and providers? This is done by using ROI and TCO for cost benefit analysis.
   • Intelligence: Ethical and legal organisation of information gathered from customers, business environment, stakeholders, business processes, competitors, and other valuable information. However, this results in too much data with little value. *Chap 4&5

6. Espionage

   • Espionage: Stealing corporate secrets.

7. Online Analytic Processing (OLAP)

   • OLAP systems are involved in extracting info from data stored by OLTP systems. OLAP extract info such as sales report by product, region, sales person etc. It's main goal is effectiveness of providing information in a timely manner. *Chap 2

8. Transaction Processing (OLTP)

   • OLTP systems are involved in handling updates (add, edit, delete) functions, aka operational databases. Eg: ATM withdrawals/deposits, sales order entry. ERP, SCM, CRM systems store data in the OLTP. It's main goal is high efficiency. OLTP handles routine on going business.

9. Successful BI implementation

   • 1. BI must be aligned with company's biz strategy. 2. Users must make use of it at strategic and tactical levels, and also with the right motivation. 3. BI should facilitate a real time, on demand, and agile environment

10. Business Analytics

    • BI generates analysis for organisations to respond to these pressures. Examples of responses are: employ analytics to aid biz decisions, strategic planning, form new business alliances, improve partnership r/s, incorporate new info systems, move to e-commerce, faster response to competitors' actions (launch of new products/promotions etc), encourage employees innovation/creativity.
    • Analysis: Develop actionable decisions/recommendations generated from historical data. Analytics are categorised under 3 levels: Descriptive, Predictive, Prescriptive.
      • Descriptive: What happened > Generate scorecards, Biz reporting, DW > Defined biz problems/opportunities. Also known as reporting analytics. For current affairs: what is happening in the org, understanding trends, causes. Involves reporting and visualisation tools to consolidate data sources and availability of all relevant data in data WH
      • 2. Predictive: Aims to determine what is likely to happen based on statistical and data mining techniques. What will happen? > Data/text/web mining, forecasting > More accurate projections.
      • 3. Prescriptive (What should i do? > optimisation, decision modelling > best possible business decisions