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Introduction to Data Management

Introduction to Data Management. Learning Objectives. Understand: meaning of data management history of managing data challenges in managing data approaches to managing data data strategy data life cycle data architecture sources and methods for collecting organizational data.

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Introduction to Data Management

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  1. Introduction to Data Management

  2. Learning Objectives Understand: • meaning of data management • history of managing data • challenges in managing data • approaches to managing data • data strategy • data life cycle • data architecture • sources and methods for collecting organizational data

  3. What is Data Management? General Definition • Developing plans, processes, and systems to ensure data is: • Relevant • Accurate, Timely • Available • Secure • Shareable

  4. Historical Context: Automating Processes in Organizations

  5. Need for Focus on Data Management _______ is an asset to be planned, managed, and protected, and when converted to ___________ & ___________, gives the firm competitive advantages

  6. Historical Context: Managing Data in Organizations • Centralized Data Management • Emerged in the 1970s; became popular in the 1980s • Helps avoid many problems with process-centered development • Provides integration between applications through a common database Inventory GeneralLedger Database Marketing Personnel

  7. Data, Data, & More DATA!!! ??? • 90's and beyond: • "Silos" • Heterogeneous • Duplicated ERP Database ERP (Inventory) ERP (GeneralLedger) Database Gov't, Industry Codes Marketing Personnel Clickstream Data…

  8. Data Management Challenges • The amount of data increasing exponentially with time • What’s relevant? • Data security, quality, and integrity more complex • Applying enough resources? • Data are scattered throughout organizations • Where is it? • How is it stored? • Data management and analysis tools can be a challenge • SO many! • Ease of use varies

  9. Data Management Challenges • The amount of data increases exponentially with time • What’s relevant?  Modeling Data Requirements • Data security, quality, and integrity are critical • Applying enough resources?  Designing and Securing Data Structures  Data Cleansing, Transforming • Data are scattered throughout organizations • Where is it?  Integrating Data (eg, DB, CRM Systems) • How is it stored? • Data management & analysis tools can be a challenge • SO many!  Use of popular DBMS and CRM tools • Ease of use varies

  10. Adapted from Data Strategy topic, Dr. Tanner What is Data Management? Data Strategy Perspective

  11. Data Sources • Internal (Organizational) Data Sources • stored in the corporate database • info about people, products, services, processes, transactions • Personal (Individual) Data • business data stored in personal data files • business rules • business data • individual ideas, opinions • ideas about product improvement • estimates of sales • opinions about competitors • External (Environmental) Data Sources • commercial databases • government databases, reports • sensor data • clickstream data • vendor lists, …

  12. Data  Collection Methods • Internal data • Transaction processing systems (TPS’s, Web applications) • Individual data • Interviews of users • Time studies • Surveys • Observations • Contributions from experts… • External data • Instruments and sensors • Benchmarks • Web sites (counters, clickstream) • Purchased data

  13. Data (Integration) Architecture

  14. Data Integration Architecture Example Game Machines Customer Activity DB (Operational Data Store and/or Data Marts) Organization Analysis DB (Data Warehouse) Hotel Reservations Event Management Offers Redeemed • Pre-defined reports • Ad-hoc queries • Customer lookups • Campaign Management • Generate Marketing Lists • etc… Managerial Applications • Market Segmentation Analysis • Customer Profiling • Generating Marketing Lists • etc… Web Activity External Data (Marketing Lists, Prospects,…) Apps DB

  15. What is Data Management?General Definition Revisited • Developing plans, processes, and systems to ensure data is: • Relevant • Accurate • Timely • Secure • Available • Accessible • Shareable How do we identify and organize data that’s important to us? How do we ensure the quality, integrity of this data? How do we restrict access to this data to those who need it? How do we ensure data can be easily maintained, shared, and analyzed?

  16. Summary: It’s All About Data Data Information Knowledge Basis for Decisions, Competitive Advantage • Why is data management important to organizations? • How was data managed in the past? How is data managed now? • What challenges exist in managing data? • Data life cycle: collect – store – access & analyze • Data Collection sources and methods • Data Storage – databases, data marts, data warehouses • Data Access – intranet, web browsers, middleware • Data Analysis (Business Intelligence) – queries, OLAP, • data mining, DSS/EIS… • Role of data architecture

  17. Next Time… • 1/21 – 1/30 Data Modeling • 2/04 * Data Modeling Quiz *

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