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CS 543 Data Warehousing

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New technologies (multidimensional modeling, business intelligence, OLAP, querying models, etc) ... in large scale data analysis and business intelligence ... – PowerPoint PPT presentation

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Title: CS 543 Data Warehousing


1
CS 543 Data Warehousing
  • Course Outline

2
Data Warehousing?
  • What is data warehousing?
  • A paradigm specifically designed for strategic
    business information or decision making
  • In essence, data warehousing is a data-driven
    decision-support system
  • What is a data warehouse?
  • It is an informational environment with the
    following characteristics
  • provides an integrated and total view of the
    enterprise (data), current and historical, and
    makes it available easily for decision support
  • decision support transactions do not impact
    operational systems
  • maintains a consistent view of enterprise
  • provides flexible and interactive source of
    strategic information

3
Why Study DW?
  • New technologies (multidimensional modeling,
    business intelligence, OLAP, querying models,
    etc)
  • Research potential (data mining, business
    intelligence, ETL algorithms, multidimensional
    data analysis, query optimizations, etc)
  • Industry demand
  • High market value of DW experts
  • Fulfill degree requirements
  • Easy course, want to sleep through it )

4
Description
  • This course will
  • cover the concepts and techniques in the design
    and construction of high-performance data
    warehouses
  • discuss business, software, hardware, and design
    factors influencing successful implementations of
    data warehouses
  • focus on both dimensional and relational data
    modeling
  • Distinguish between DSS (Decision Support System)
    and OLTP
  • Introduce OLAP and ETL algorithms and systems
  • Provide hands-on experience with data warehousing
    tools

5
Goals
  • Introduction to the concepts and techniques in
    data warehousing
  • Design and construction of high performing data
    warehouses
  • Hands-on experience with a commercial data
    warehousing tool (Teradata)
  • Motivation for research in large scale data
    analysis and business intelligence

6
Before Taking This Course
  • You should be comfortable with
  • Basics of databases
  • CS 341 is a prerequisite
  • Fundamentals of RDMS EER modeling concept of
    normalization querying design and development
    exposure
  • Basics of programming and algorithms
  • CS 213 is a prerequisite
  • Understanding, evaluating, and implementing
    algorithms

7
After Taking this Course
  • You should be able to
  • Design and construct data warehouses
  • Understand the concepts and techniques in data
    warehousing
  • Use a data warehouse to extract strategic
    information
  • Pursue further studies and research in data
    warehousing, large data analysis, business
    intelligence, and data mining
  • Work with a commercial data warehousing tool

8
Grading
  • Points distribution
  • Labs/Assignments 20
  • Quizzes 15
  • Midterm exam 30
  • Final exam (comprehensive) 35

9
Policies (1)
  • Quizzes
  • Quizzes may or may not be announced. If a quiz is
    announced it will be done 1 to 2 days in advance
  • Sharing
  • No copying is allowed for labs/assignments.
    Discussions are encouraged however, you must
    submit your own work
  • Violators can face mark reduction and/or reported
    to Disciplinary Committee for action
  • Plagiarism
  • Do NOT pass someone elses work as yours! Write
    in your words and cite the reference. This
    applies to code as well.
  • Violators can face mark reduction and/or reported
    to Disciplinary Committee for action

10
Policies (2)
  • Submission policy
  • Submissions are due at the day and time specified
  • Late penalties 1 day 10 2 day late 20
    not accepted after 2 days
  • An extension will be granted only if there is a
    need and when requested several days in advance.
  • Rechecking policy
  • For quizzes and labs/assignments No recheck
    request will be entertained after 2 days of
    return
  • For midterm exam No recheck request will be
    entertained after 5 days of return (and should be
    made at the time of collection)
  • For final exam No recheck request will be
    entertained after start of next quarter

11
Summarized Course Contents
  • DW fundamentals, need for a DW, decision support
    vs. transaction processing, evolution of a DW
  • Business requirements as the driving force for
    the DW, matching information to classes of users
  • Dimensional modeling
  • Architecture and Infrastructure, data extraction,
    transformation and loading, data quality
  • Selected de-normalizations, horizontal and
    vertical partitioning, materialized views
  • Physical design
  • Data mart design, web data warehousing
  • Current topics in data warehousing

12
Course Material
  • Primary text
  • P. Ponniah, Data Warehousing Fundamentals, John
    Wiley Sons, 2001.
  • Supplementary text
  • C. Imhoff et al., Mastering Data Warehouse
    Design Relational and Dimensional Techniques,
    John Wiley and Sons, 2003.
  • Other resources
  • Lecture slides
  • Handouts
  • Web resources
  • Books in library

13
Course Web Site
  • For annuncements, lecture slides, handouts, labs,
    assignments, quiz solutions, and web resources
  • http//suraj.lums.edu.pk/cs543s05/
  • The resource page has links to information
    available on the Web. It is basically a meta-list
    for finding further information.

14
Other Stuff
  • How to contact me?
  • Office hours 10.30 to 12.30 MW (office 429)
  • E-mail akarim_at_lums.edu.pk
  • By appointment
  • Philosophy
  • Knowledge cannot be taught it is learned.
  • Be excited. That is the best way to learn. I
    cannot teach everything in class. Develop an
    inquisitive mind, ask questions, and go beyond
    what is required.
  • I dont believe in strict grading. But there has
    to be a way of rewarding performance.

15
Pakistani Students
  • It was good to see that the students were quite
    good at abstract discussions and given my
    teaching experience at foreign universities, I
    would rate the batch I taught as competitive.
  • My advice to Pakistani students is that they
    need to become aggressive learners and realise
    that a university education assumes that the
    student is mature enough to take control of his
    or her destiny.
  • - Dr. Raja Muhammad Atif Azad, Lemerick, Ireland
  • Appeared in Dawn http//www.dawn.com/2006/03/02/l
    etted.htm4

16
Reference Books in LUMS Library (1)
  • C. Imhoff et al., Mastering the data warehouse
    relational and dimensional techniques, Wiley,
    2003.
  • W. Inmon, Building the data warehouse, Wiley,
    2005.
  • R. Kimball, The data warehouse toolkit the
    complete guteide to dimensional modeling, Wiley,
    2002.
  • R. Kimball, The data warehouse ETL toolkit
    practical techniques for extracting, cleaning,
    conforming, and delivering data, Wiley, 2004.

17
Reference Books in LUMS Library (2)
  • Building, using, and managing the data warehouse,
    Barquin, Ramon C., ed.Edelstein, Herbert A.,
    ed., 005.74 B932, 1997.
  • Data warehousing and business intelligence for
    e-commerce, Simon, Alan R.Shaffer, Steven L.,
    658.84 S594D, 2001.
  • Data warehousing for e-business, Inmon, W. H.
    Terdeman, R. H. Norris-Montanari, Joyce Meers,
    Dan, 658.84 D232, 2001.
  • Data warehousing in the real world a practical
    guide for building decision support systems,
    Anahory, Sam Murray, Dennis, 005.74 A532D, 2000.
  • Data warehousing concepts, techniques, products
    and applications, Prabhu, C.S.R., 005.74 P895D,
    2002.
  • Data warehousing strategies, technologies, and
    techniques, Mattison, Rob, 658.4038 M444D, 1996.
  • Introduction to business intelligence and data
    warehousing, IBM, Prentice-Hall of India, 658.47
    I619 2004

18
Reference Books in LUMS Library (3)
  • Data warehousing the ultimate guide to building
    corporate business intelligence, Educations B.
    V., SCN., ed., 005.74 D232, 2001.
  • Decision support in the data warehouse, Gray,
    PaulWatson, Hugh J., 005.74 G778D, 1998.
  • Intelligent data warehousing from data
    preparation to data mining, Chen, Zhengxin,
    005.74 C518I, 2002.
  • The data webhouse toolkit building the
    web-enabled data warehouse, Kimball, Ralph Merz,
    Richard, 005.74 K495D, 2000.
  • Oracle8i data warehousing plan, Corey, Michael
    ... et al., 005.7585 O631, 2001.
  • Data warehousing with Oracle an administrator's
    handbook, Yazdani, SimaWong, Shirley S., 005.74
    S588D, 1998.
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