The MultiDimensional Model Need for MDM Notions of
- Slides: 19
The Multi-Dimensional Model Need for MDM Notions of Facts and Dimensions Representing MDM as Star Schema
The Problem Data warehouses need a model of data that is specific to supplying information Requirements Engineering Model must provide a logical view of data and interrelationships The relational model is good for recording transactions but not for decisional analysis Need a data warehouse conceptual model Requirements Engineering deals with needs, not with how they are met The Information Model must be converted into the data warehouse conceptual model Conceptual Design
The Model Driven Architecture of OMG Relates to business needs Platform Independent Model Platform Specific Model Conceptual Design (Multi-dimensional Model) Logical Design (MOLAP/ROLAP Hyperion SQL server
Why Multidimensional Data Model? Decision: Reward the client who buys maximum amount of all products Information: amount in rupees for each client product wise Fact relation No clear view, dump of data Query can be formulated, of course but unclear model Two-dimensional structure The product-client interaction is clear
Multidimensional Data Model Fact relation 3 -dimensional cube date 2 date 1 Decision: Reward client buying both products in a day
Why Multidimensional Data Model? In general, let there be a relation of (N+M )attributes of which M are measures. We get N dimensional space with each cell containing M measures Example Sale(Product, Client, Salesperson, Date, Amount sold, Quantity Sold) Gives 4 -dimensional space with Product, Client, Salesperson, Date as dimensions Amount sold, Quantity Sold as facts Ease of Querying/Analysis is done on the cells that are located by supplying values to dimensions Clear identification of the data and the parameters of analysis
Dimensional Modelling For conceptualizing and visualizing data models as a set of measures described by common aspects of the business. Dimensional modeling has two basic concepts: · · Facts Dimensions Other related concepts · · Aggregates Meta-data
Fact: Definition Different but complementary definitions of facts – A fact is a collection of related data items, consisting of measures – A fact is a focus of interest for the decision making process. – Measures are continuously valued attributes that describe facts – A fact is a business measure A fact answers the questions What exactly is being analysed? What numbers are being analysed?
Fact in the Business World Analyse a business process. Each fact typically represents • a business item: an order • a business transaction: order processing • an event: arrival of an order Facts: Only those business concepts found useful in analyzing the business/business processes.
Facts: Examples A university provides education services to its students. It is trying to increase revenue from the admission process. What are its facts and measures? Facts Measures Applications number, revenue from prospectus sales Enrollment number, revenue
Facts: Examples A university wants to identify students with highest CGPA and best placement package for distributing awards. What are its facts and measures? Facts Measures Student Performance grades, marks, %age marks, division Student Placement designation, nature of job, salary Student awards Title, amount
Some Properties of Facts A fact is continuously valued. It takes a value from a a broad range of values. The set of integers real numbers The most useful facts are numeric and additive Amounts can be added Quantities can be added Textual facts occur very rarely: free format and unpredictable contents make it impossible to analyse these recent interest in unstructured DW look at these
Dimension Definition • The parameter over which we want to perform analysis of facts Sales is a fact; perform analysis over region, product, time • The parameter that gives meaning to a measure number of customers is a fact, perform analysis over time cannot perform analysis over product Discretely valued description that is more or less constant and participates in constraints Qualifying characteristics that provide additional perspective to a given fact
Examples of Dimension A university provides education services to its students. What are its facts and dimensions? Facts Dimension Applications Age, Region Enrollment Region Performance Year, Course, Student Placement Year, Discipline, Grades Student awards Discipline, Year
Dimensions and their Values Dimension Value Age 10, 11, 12 …. . Region North, South Year 1999, 2000 …. Discipline ECE, CSE, IT, . . . Grades A+, A, …. Student ABC, Ram, Sita, Geeta Dimension Attributes Name ; Roll No Sachin 2017001 Rama 2017002 Sita 2017003
The Star Schema Shows explicitly the link between a cell of a cube and its dimensions Highly oriented to relational implementation: use of foreign keys between fact and dimension relations Dimension Fact Dimension
Example: Facts and Dimensions Course ID Name Student Performance Student Roll No Marks; Grade Student Name Year
Identify Facts and Dimensions MTNL wants to improve its Quality of service. It wants to do so by bringing the number of complaints down. It has 30, 000 line exchanges at NOIDA, Shakti Nagar, and Janpath. There are different kinds of defects reported: no dial tone, no incoming, no outgoing etc. These amount to a total of 50 different defects. It is required to keep track of defects for the last 5 years.
Exercise An annual tree plantation drive is held in a district. A district has taluk, blocks, villages. The tree plantation organization distributes saplings of different kinds to different people and wants to analyze the survival rate of plants. Build a data warehouse. Depending on climate survival changes, time of plantation, soil quality.
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