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INFO102: Introduction to IS Business Intelligence part 1

Objectives ? next 2 lectures. Describe the evolution of data warehousingDefine ?data warehouse" and ?business intelligence" (BI)Describe the benefits that organizations get by implementing BIProvide an overview about how BI workDemonstrate some BI tools. New Wave ? information analysis needs. Ne

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INFO102: Introduction to IS Business Intelligence part 1

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    1. INFO102: Introduction to IS Business Intelligence – part 1

    2. Objectives – next 2 lectures Describe the evolution of data warehousing Define “data warehouse” and “business intelligence” (BI) Describe the benefits that organizations get by implementing BI Provide an overview about how BI work Demonstrate some BI tools

    3. New Wave – information analysis needs New Wave successfully implemented new online design and sales system After 4 weeks, there appears to be lots of traffic on the site (based on how busy servers are) – but only a few sales so far Managers in finance, sales, web marketing and manufacturing are very anxious to get information so they can assess how things are going now, determine if there are any issues and plan for future.

    4. New Wave - Systems

    5. Data Warehousing Evolution and Definition

    6. The Evolution of Data Warehousing 1970s: organizations start to use computers to run their business….start to collect lots of transactional data 1980s: PCs start appearing on desktops – users start using spreadsheet software to analyze data from operational systems – lots of problems.

    7. The Evolution of Data Warehousing 1990s: businesses start to recognize that using information effectively can give them a competitive advantage (Walmart!)….but It is very difficult to access and integrate data locked away in operational systems (example later) Operational systems not designed to handle the demand for information access The data from various operational systems overlap and often contain contradictory definition of data 1990s: businesses see the value of an integrated store of information to support decision making 1990s: Hardware and storage costs plummet while computing power doubles every 18 months: Makes it feasible to store AND analyze vast amounts of data

    8. The Evolution of Data Warehousing 1990s: The DEMAND for integrated data for analysis converged with the TECHNICAL FEASIBILITY of storing and accessing this information, resulting in:

    9. Scenario The marketing department at the Bank of Nova Scotia wants to execute a marketing campaign aimed at increasing the loyalty of the banks best customers (those with portfolios more than $500,000). The analysts wants find the following information. Identify those customer that have more than $500,000 in loans, deposits and investments who have responded to at least one previous marketing campaign. Send a letter to each customer, offering a new investment product at a preferred rate Determine who responded to the marketing offer by purchasing the investment product during the bank’s 3rd fiscal quarter

    10. Scenario - Systems

    11. The Answer In reality, this scenario could not be carried out without some form of data warehouse because: Queries would take days or weeks to create and perfect. The technical skills and knowledge required to construct the queries would require a team, not just one individual. Queries performance would be excruciatingly slow (days?) Performance of operational systems would be adversely impacted There would be numerous data integrity issues to overcome.

    12. Data Warehouses

    13. Data Warehouse – Definitions A data warehouse is a type of computer based information system developed to provide an organization with business intelligence to support decision making and to monitor the operations in a company. Integrates data from many different sources and makes it available to end users in a what they can understand and use in a business context. It’s a repository of data designed specifically for reporting and analysis…..the design is very simple A process of transforming data from different sources into information and making it available to users in a timely manner.

    14. Data Warehouse: Extended Definition

    15. Main Characteristics of a Data Warehouse

    16. Subject Oriented Operational systems are functionally/process oriented and concerned with what is happening now: Web traffic, sales, manufacturing Data warehouses are organized around data subjects and all data for a subject is linked together: For a given customer: all web traffic, sales, payments, complaints, board designs, etc. The Data Warehouse keeps a history for each subject Corporate memory Data warehouses retain data for each subject that is useful for analysis purposes

    17. Integrated Data in the Data Warehouse is always integrated – integration is one of the key services provided by a DW Integration means: Consistent definitions Consistent naming conventions Consistent measurements (inches – yards – centimeters) Consistent encoding (male/female) The process of building the data warehouse corrects the inconsistencies found in operational systems – often this is the biggest challenge in developing the data warehouse

    18. Time The data in the data warehouse consists of a series of periodic ‘snapshots’. It is accurate as of a moment in time (the time the data was extracted from the operational environment). Detailed data in the warehouse has an element of time in the key structure Time horizon in the warehouse is years (vs. weeks or months in an operational system)

    19. Non-Volatile Operational data is very volatile Data warehouse data is non-volatile: once data is loaded into the warehouse, it does not change (unless loaded in error). Simplifies the design of the data warehouse: Only needs to handle periodic loads, rather than constant updates

    20. Warehouse Data: Designed to be simple

    21. Multidimensionality

    22. What is business intelligence? organized information that helps individuals in an organization make better, more informed decisions more quickly.  Business intelligence is generated from a data warehouse, which collects, stores and presents data.  Business intelligence systems customize information output to be the most useful for the intended audience.  The overarching goal of business intelligence is:  to provide individuals within the organization with the right information, in the right format at the right time to facilitate faster, better decisions.

    23. What is business intelligence? (cont)

    24. Business Intelligence Benefits

    25. Immediate Access to Information Data warehouses shrink the length of time it takes between when business events occurrence and alert of appropriate person. Business people don’t need to use spreadsheets to manually integrate information For example, in many corporations, sales reports are printed once a month - about a week after the end of each month. Thus, the June sales reports are delivered during the first week in July. Using a warehouse, those same reports are available on a daily basis. Given this data delivery time compression, business decision makers can exploit opportunities that they would otherwise miss.

    26. Data integration from across, and even outside, the organization To provide a complete picture, warehouses typically combine data from multiple sources such as a company's order entry and warranty systems. Thus, with a warehouse, it may be possible to track all interactions a company has with each customer - from that customer's first inquiry, through the terms of their purchase all the way through any warranty or service interactions. This makes it possible for managers to have answers to questions like, "Is there a correlation between where a customer buys our product and the amount typically spent in supporting that customer?"

    27. Future vision from historical trends Effective business analysis frequently includes trend and seasonality analysis. To support this, warehouses typically contain multiple years of data Also, warehouses are designed to do time-based (temporal, longitudinal) analysis

    28. Tools for looking at data in new ways Instead of paper reports, warehouses give users tools for looking at data differently. They also allow those users to manipulate their data. There are times when a color coded ‘speedometer’ speaks volumes over a simple paper report. An interactive table that allows the user to drill down into detail data with the click of a mouse can answer questions that might take months to answer in a traditional system.

    29. Looking at data in new ways

    30. Freedom from IS department resource limitations One of the problems with computer systems is that they usually require computer experts to use them. When a report is needed, the requesting manager calls the IS department. IS then assigns a programmer to write a program to produce the report. The report can be created in a few days or, in extreme cases, in over a year. With a warehouse, users create most of their reports themselves. Thus, if a manager needs a report for a meeting in half an hour, they, or their assistant, can create that report in a matter of minutes.

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