Data Warehouse and Data Mining

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1 Data Warehouse and Data Mining Lecture No. 09 Plannning Data Warehouse Naeem Ahmed Department of Software Engineering Mehran Univeristy of Engineering and Technology Jamshoro

2 Planning Improper planning and inadequate project management tend to result in failures Major issue Following aspects need to be considered: Determine if company really needs a data warehouse. Is it really ready for one? Decide on the type of data warehouse to be built and where to keep it? Who will be using the data warehouse and at what times?

3 Requirement Analysis There are three principal reasons for performing a requirements analysis: Getting the system right the first time. Supporting easy user access to the system Producing reasonable and reliable estimates of costs Without a requirements analysis, one cannot have any grasp of how much an IT project will cost.

4 Interviewing for Requirements Interviewing enterprise management and end users provides insights into the actual use of the data that cannot be obtained in any other way Among the factors that must be determined by the process are the following: How best to input data How best to report information from the database How management interprets and analyzes the reports it receives from the database

5 Determine who should be Interviewed What sorts of users should be included in interview pool? The following list is a bare minimum: Speak with people involved in the process of the business. Talk to vendors if plan is to use Supply Chain Management and Customer Relationship Management applications. Talk to enterprise management about their information needs including what sorts of reports, queries, and data mining capabilities they require. The objective is not to determine how to get those answers, but to determine what sorts of answers they think they would like to get whether it is possible or not. Talk to end users about what they need, what problems they have with legacy systems, and obtain their wish lists of features, interfaces, and processes

6 Interviewing Techniques and Personal Agendas to Consider Always keep the objective of the interview in mind, which is to learn about the business Conduct user and management interviews separately This should be done not only because of the unavoidable intimidation factor, but also because the two groups have different perspectives on the issues When possible, arrange for 1:1 interviews. If not, keep interview groups as small as possible, preferably no more than five people Keep the number of interviewers small: generally no more than two per session Approach the design as if no knowledge of the enterprise or its data model is available Listen actively

7 Interviewing Techniques and Personal Agendas to Consider Before beginning, explain what the interview process is. Tell subjects what to expect and what is expected from them. Thank them for their time and make certain they understand that their observations will be taken into consideration Have a prepared list of questions. Stay on track, but do not hesitate to ask aggressive follow-up questions where an answer raises an important issue. When finished, follow up where necessary for clarification and expansion. Ask open-ended questions. Not like: Is the daily sales system a) not adequate b) barely adequate c) adequate d) excellent, but like: How do you feel about the daily sales system? Take thorough notes or tape record the session

8 Interviewing Techniques and Personal Agendas to Consider If facilities are available and the procedure would not be obtrusive, consider videotaping sessions Review and summarize notes or taped transcription as soon as possible after the completion of each interview Take control of the interview and maintain it, arbitrating any disagreements among participants that may arise, and keeping things moving at all times Stay on track When the interview is finished, thank the participants for their assistance in the process and acknowledge the importance of their input

9 Analyzing a Legacy Database To analyze the existing database for its strengths, weaknesses, uses and to develop a list of what needs to be retained, what needs to be changed, and what needs to be eliminated Analyze the legacy system both from an end user perspective and from an IT perspective

10 Terminologies Attribute: Named column in a relation Relation: A table with rows and columns Tuple: A tuple is a row of a relation Degree: In a relation, number of attributes it contains Cardinality: In a relation, number of tuples it contains Super key: An attribute or set of attributes that uniquely define each record within a relation Candidate key: A superkey such that no proper subset is a superkey within the relation Super key is the superset of Candidate key

11 Terminologies Primary key: The candidate key that is selected to identify tuples uniquely within the relation Composite key: A candidate key that has more than one attribute Foreign key: An attribute, or set of attributes, within one relation that matches the candidate key of some (possibly the same) relation Surrogate key: A unique identifier for either an entity in the modeled world or an object in the database i.e., system generated sequence number.

12 Requirements to Data Design

13 Requirements to Data Design Before proceeding dimensional modeling, make design decisions: Choose process: Subject for Data warehouse Granularity Level: Level of details Identify Dimensions Identify and choose Facts Time duration: Decide the time for updating Data warehouse Information packages: The data that shows the business parameters, rules, hierarchies and measures

Data Warehouse and Data Mining

Data Warehouse and Data Mining Lecture No. 05 Data Modeling Naeem Ahmed Email: naeemmahoto@gmail.com Department of Software Engineering Mehran Univeristy of Engineering and Technology Jamshoro Data Modeling