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Data Resource Management MGMT 4170 Lally School of Management Data Structures in Organizations.

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Presentation on theme: "Data Resource Management MGMT 4170 Lally School of Management Data Structures in Organizations."— Presentation transcript:

1 Data Resource Management MGMT 4170 Lally School of Management Data Structures in Organizations

2 Market Insight The United States faces a shortage of close to 200,000 people with business analytics expertise. The U.S. Department of Labor forecasts that the number of analytics-based jobs will grow by more than 20% between now and 2018. 40% of organizations report a skills shortage in the ability to manage information. 1 in 3 frequently make critical decisions without the information they need or trust. Source: IBM

3 What is a Business?

4 Understanding Organizational Structure Human Resources SalesMarketingFinanceProduction

5 The Operational, Tactical, and Strategic Areas of Data and Information Processing Strategic Tactical Transactional/Ops The role of each level is very different: -Strategic Objectives -Implementation -Transaction Processing

6 Application Layer TPS System Architecture Data Layer Sales/MarketingHR Finance/Accounting Operations Spreadsheet Data MS Access Accounts Receivable Accounts Payable Investment Management Oracle Database Quotation Processing Order Processing Claims Processing Spreadsheet Oracle Database Foxpro Recruiting Career Planning Compensation Management Excel Production Planning Product Development Maintenance Planning Oracle Excel Oracle

7 Strategic Tactical Transactional/Ops Horizontal Movement of data -Extended Cycle Times -Transactional Cost -Inefficiency -Risk

8 Strategic Tactical Transactional/Ops Vertical Movement of data -Extended Cycle Times -Transactional Cost -Inefficiency -Risk

9 Strategic Tactical Transactional/Ops We are in the middle Strategic Tactical Transactional/Ops Strategic Tactical Transactional/Ops Strategic Tactical Transactional/Ops Strategic Tactical Transactional/Ops Suppliers Customers

10 System Architecture Extraction -Transformation - Loading Corporate Transaction Processing System Data Warehouse External Data: Suppliers External Data: Customers Relational Data Spreadsheet Data Data Mining OLAP MDX SQL

11 The role of relational databases Serve as robust transaction processing systems. Single data source for the organization. Tremendous reporting capabilities. Ability to cooperate with databases from suppliers and partners.

12 The role of ETL 88% of IT projects fail due to ETL reasons. Cannot have an efficient business without ETL. It is the key for transfer of data among TPS systems and from TPS systems to data warehouses. It is a key technology for customer-supplier-partner efficient cooperation. ETL Market Statistics.

13 The role of SQL SQL is the base language for creating database objects, maintaining objects, and retrieving information. It is a language far more capable than its reputation. It is the only language that allows information retrieval from data in TPS system based on a relational database.

14 The role of the data warehouse The number one purpose is to store historical data. They contain data from multiple heterogeneous transactional systems. Data warehouses are not data archives. They contain live data which we can query.

15 Data Warehouse Schema Fact TableDimension Tables

16 The role of OLAP/MDX Online Analytical Processing and Multi-dimensional expressions are two information processing technologies. With OLAP we get information out of the TPS or the data warehouse. MOLAP – ROLAP. We access very different data than in relational databases. They are technologies that help us create information and meta-data for more processing.

17 OLAP example

18 OLAP Cubes 100 470 300 120 Cheese Cola Milk Cream Store1 Store 2 Store 3 Unit Sales as a function of stores and product 3/1 3/2 3/3 3/4 80120130 430122550 280 250 420 100130160 Units of Milk sold in store 3 the 3 rd of March Dimensions Measure

19 The role of Data Mining Data mining is a technology used to uncover information not readily intuitive to human beings. The technology creates the information. Various algorithms are used to derive information from data. A lot of experience is needed to associate the best algorithm with the corresponding business scenario.


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