Online Data Modeling Training Syllabus

Part 1: Course Information

Course Description:

This online training course explains in detail about database, data warehouse, data modeling concepts, data modeling types and how these are used in OLTP environments and Data warehouse / Datamart Environments.

To get more information about the program, send an email to Training@LearnDataModeling.Com and we will get back to you.

Course Information:
  • Course Name: Advanced Data Modeling Training
  • Training Hours: 7.30 AM to 9.00 AM IST
  • Days: Tuesdays, Thursday, and Saturday
  • Total no. of theoretical classes: 20
  • Practical Classes: 5
  • Mode of Teaching: Online through SKYPE.
  • Instructor: Neelesh & Antony
  • Office: USA and Chennai
Course Requirements:
  • Internet connection
  • Lap Top or Desk Top
Tools:
  • Erwin
  • MS Word, MS Excel
  • My SQL
  • Windows Operating System
Training Material:
  • Soft copy of the document will be provided.
Training Certificates:
  • Will be provided.

Part 2: Topic Outline/Schedule 

Week 01: Data Modeling

  • What is a Data Model?
  • Who needs Data Modeling?
  • Different Data Modeling Tools.
  • Explanation for Logical, Physical, Conceptual, Enterprise, and Dimensional Data Model
  • Data Modeling Development Life Cycle
  • Steps to create a data model
  • Data Modeler Role

Week 02: Data Modeling Tools & Database

  • Database Commands: Database Objects, Constraints, Create Object, Alter Object, Drop Object, Insert, Delete, Update
  • Naming conventions and standards.
  • How to create a Logical Data Model?
  • How to create a Physical Data Model?
  • Comparison of Logical and Physical Data Model
  • How to generate SQL Code?
  • How to implement it in Database?
  • How to create versions of the Data Model?
  • How to compare a Data Model with a Database?
  • How to create a Data Model from a Database?
  • What is Repository?
  • What is Metadata?
  • How to generate reports?
  • What to learn in Data Modeling Tools.

Week 03: Data Warehouse and Data Mart

  • What is a Data Warehouse?
  • What is a Data Mart?
  • What is Snow Flake Modeling?
  • What is Star Schema Modeling?
  • What is Slowly Changing Dimensions?
  • What is a Lookup?
  • How to maintain data in Lookups?
  • How to send emails to your stake holders?

Week 04: Advanced Topics

  • Normalization, Advanced Topics on Data Modeling.

Week 05: Hands on practice with Erwin and MySQL

  • Hands on practice with different scenarios.

Business Intelligence Tutorial

Business Intelligence & Metadata Tutorial:

Business Intelligence is a terminology refers to taking advantage of data and converting them into an intelligent information or knowledge by carefully observing data patterns or trends. These findings are key factors in helping any business to improve it’s current business processes to gain more on customer satisfaction, increase sales, produce more profit etc. The knowledge observed from several report based analysis may lead to new business changes or improvements thus helping the organization to grow in the targeted direction. Browse through the various topics listed below to know more.

Advantages of Multi Dimensional Databases

OLAP Database – Multidimensional:

This is a type of database that is optimized for data warehouse, data mart and online analytical processing (OLAP) applications. The main advantage of this database is query performance.

Relational databases make it easy to work with individual records, whereas multidimensional databases are designed for analyzing large groups of records. Relational database is typically accessed using a Structured Query Language (SQL) query. A multidimensional database allows a user to ask questions like “How many mortgages have been sold in New Jersey city” and “How many credit cards have been purchased in a particular county?”.

Popular Multidimensional Databases:

Database NameCompany Name
Crystal HolosBusiness Objects
Hyperion EssbaseHyperion
Oracle ExpressOracle Corporation
Oracle OLAP OptionOracle Corporation
AWMicrosoft Analysis ServicesMicrosoft
PowerPlay EnterpriseCognos

 

OLAP and OLAP Hybrids

OLAP & its Hybrids:

OLAP, an acronym for Online Analytical Processing is an approach that helps organization to take advantages of DATA. Popular OLAP tools are Cognos, Business Objects, Micro Strategy etc. OLAP cubes provide the insight into data and helps the topmost executives of an organization to take decisions in an efficient manner.

Technically, OLAP cube allows one to analyze data across multiple dimensions by providing multidimensional view of aggregated, grouped data. With OLAP reports, the major categories like fiscal periods, sales region, products, employee, promotion related to the product can be ANALYZED very efficiently, effectively and responsively. OLAP applications include sales and customer analysis, budgeting, marketing analysis, production analysis, profitability analysis and forecasting etc.

ROLAP:

ROLAP stands for Relational Online Analytical Process that provides multidimensional analysis of data, stored in a Relational database (RDBMS).

MOLAP:

MOLAP (Multidimensional OLAP), provides the analysis of data stored in a multi-dimensional data cube.

HOLAP:

HOLAP (Hybrid OLAP) a combination of both ROLAP and MOLAP can provide multidimensional analysis simultaneously of data stored in a multidimensional database and in a relational database (RDBMS).

DOLAP:

DOLAP (Desktop OLAP or Database OLAP)provide multidimensional analysis locally in the client machine on the data collected from relational or multidimensional database servers.

 

OLAP Analysis

OLAP Analysis:

Imagine an organization that manufactures and sells goods in several States of USA which employs hundreds of employees in its manufacturing, sales and marketing division etc. In order to manufacture and sell this product in profitable manner, the executives need to analyse (OLAP analysis) the data on the product and think about various possibilities and causes for a particular event like loss in sales, less productivity or increase in sales over a particular period of the year.

During the OLAP analysis, the top executives may seek answers for the following: 

1. Number of products manufactured.

2. Number of products manufactured in a location.

3. Number of products manufactured on time basis within a location.

4. Number of products manufactured in the current year when compared to the previous year.

5. Sales Dollar value for a particular product.

6. Sales Dollar value for a product in a location.

7. Sales Dollar value for a product in a year within a location.

8. Sales Dollar value for a product in a year within a location sold or serviced by an employee.

OLAP tools help executives in finding out the answers, not only to the above mentioned measures, even for the very complex queries by allowing them to slice and dice, drill down from higher level to lower level summarized data, rank, sort, etc.

Example of OLAP Analysis Report:

Time Dimension IdLocation Dimension IdProduct Dimension IdOrganization Dimension IdSales DollarDateTimeStamp
11100001110001/1/2005 11:23:31 AM
3110000117501/1/2005 11:23:31 AM
11100001210001/1/2005 11:23:31 AM
3110000127501/1/2005 11:23:31 AM

In the above example of OLAP analysis, data can be sliced and diced, drilled up and drilled down for various hierarchies like time dimension, location dimension, product dimension, and organization dimension. This would provide the topmost executives to take a  decision about the product performance in a location/time/organization. In OLAP reports, Trend analysis can be also made by comparing the sales value of a particular product over several years or quarters.

 

Business Intelligence Tools

Business Intelligence Tools:

Business Intelligence Tools help to gather, store, access and analyze corporate data to aid in decision-making. Generally these systems will illustrate business intelligence in the areas of customer profiling, customer support, market research, market segmentation,
product profitability, statistical analysis, inventory and distribution analysis.

With Business Intelligence Tools, various data like customer related, product related, sales related, time related, location related, employee related etc. are gathered and analysed based on which important strategies or rules are formed and goals to achieve their target are set. These decisions are very efficient and effective in promoting an Organisation’s growth.

Since the collected data can be sliced across almost all the dimensions like time,location, product, promotion etc., valuable statistics like sales profit in one region for the current year can be calculated and compared with the previous year statistics.

Popular Business Intelligence Tools:

Tool NameCompany Name
Business ObjectsBusiness Objects
CognosCognos
HyperionHyperion
MicrostrategyMicrostrategy
Microsoft Reporting ServicesMicrosoft
CrystalBusiness Objects

 

Advantages of Business Intelligence

Business Intelligence:

Business Intelligence is a technology based on customer and profit oriented models that reduces operating costs and provide increased profitability by improving productivity, sales, service and helps to make decision making capabilities at no time. Business Intelligence Models are based on multi dimensional analysis and key performance indicators (KPI) of an enterprise.

Business Intelligence applications that are based on Business Intelligence Models are created by Business Intelligence software which provides the aggregated details about suppliers, customers, internal activities, business to business transactions to the managers or whoever needs it to take better corporate decisions.

Many business questions or situations need to be analyzed in order to achieve the target of an enterprise with the help of several managers or executives in each cadre. Below are some of the samples of these questions.

» Business Intelligence in Finance:

What is the net income, expenses, gross profit, and net profit for this quarter/year?

» Business Intelligence in Accounts:

What is the sales amount this month and what is the outstanding pending payment?

» Business Intelligence in Purchase:

Who is the vendor to be contacted to purchase products?

» Business Intelligence in Production:

How many products are manufactured in each production unit today/weekly/monthly?

» Business Intelligence in Sales:

How many products have been sold in each area today/weekly/monthly?

» Business Intelligence in Quality:

How many products have been defective today/weekly/monthly/quarterly/yearly?

» Business Intelligence in Service:

Are the customers satisfied with the quality?

These business intelligence questions are related with why, what, how, when, and business intelligence reports (olap reports) are useful in providing solutions to the above questions by means of reporting, score cards, balance score cards that are helpful in managerial decisions.

 

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