Use ‘Active’ Model Templates to facilitate reusable modeling metadata and to implement/enforce enterprise standards
Erwin Data Modeler is now certified to work with: Db2 z/OS v12 SQL Server 2019 PostgreSQL v9.6.15, v10.10 and v11.5 Oracle 18c (18.3)
Erwin Data Modeler now supports the new features and capabilities offered in Db2 LUW 11.1 like: Storage Group object support has been added. Table properties for all three types (Permanent, Global Temporary, and Nickname) have been updated. Also, Index and XML Index support has been enhanced. Tablespace properties have been updated to support Storage Space Name and Data Tag. Materialized query table properties have been enhanced.
Erwin DM Scheduler: Enables users to define and schedule database reverse engineering (REDB) tasks in advance Minimizes workstation contention by allowing modelers to plan for and run REDB tasks when resources are available
Overall modeler productivity has been enhanced via new product functionality and workflows: A “quick” compare option set and “speed” option Supertype-Subtype transformation updated to retain separate logical and physical constructs for Identity and Roll-Up option selections Deletion of a relationship offers modeler the option of converting migrated FK attribute(s)/column(s) into child entity/table owned attribute(s)/column(s) Mart OPEN dialog now displays number of entities, attributes and relationships Mart and mart report performance has been significantly improved Database “Target server” dialog can be accessed by clicking the database name displayed on the physical model status bar
Naming Standards enhanced to fully support physical-to-logical name mapping
Users defined in Azure Active Directory can now connect to the Mart from erwin Data Modeler.
Erwin Data Modeler now offers an automation option for Reverse Engineering and Forward Engineering through the Erwin API.
Erwin Data Modeler includes flexible extended notes on all object types that can be: compared, searched, and edited using the Bulk Editor reported via the Report Designer managed using the erwin API
Erwin SCAPI has been extended to support the application of naming standards.
Erwin Data Modeler provides “native” support for Hadoop Hive as a database target – including AVRO files!
Licensing improvements include: Silent Install Option to “hide” Licensing dialog Support for proxy connections to the License/Activation server Optional network domain name and subnet IP-based usage restrictions erwin Data Modeler “edition”-based licensing The ability to “borrow” (Long Term Check Out) cloud-based concurrent licenses
Collaboratively administer the Workgroup Edition mart using our web-based Mart Administration utility Session (Offline/Disconnect) Management Security (User/Role) Management AD Authentication (via LDAP) Permission/Authorization Management Model Locking
Collaboratively administer the Workgroup Edition mart using our web-based Mart Administration utility Session (Offline/Disconnect) Management Security (User/Role) Management AD Authentication (via LDAP) Permission/Authorization Management Model Locking
Erwin Data Modeler supports a wide variety of reports from a mart, including: administrative cross-model model object count reports
The erwin Data Modeler (DM) User Interface has been revamped to include the following: A Microsoft “Office-like” ribbon-based appearance UI themes, font sizes, and component direction settings Tabbed and “side-by-side” diagram window arrangement option A “Quick Access” toolbar
Erwin Data Modeler supports both online and local product documentation and help.
Erwin Data Modeler has added “native” support for Redshift as a database target.
Report Designer includes the ability to create customized report filters and properties using erwin Data Modeler’s TLX scripting language
Erwin Data Modeler supports new features and capabilities offered in SQL Server like: Always Encrypted columns Dynamic Data Masking Temporal tables Memory Optimized Table Natively compiled Stored Procedures
Erwin Data Modeler supports new features and capabilities offered in SQL Server like: Always Encrypted columns Dynamic Data Masking Temporal tables Memory Optimized Table Natively compiled Stored Procedures
User enhancements and modeling improvements include: A new option has been added to allow modelers to enforce Relationship Nullability Rules A new option has been added to allow modelers to enforce Supertype-Subtype relationship rules Oracle 12c support for 128 character TABLE and COLUMN Names and PostgreSQL support for 63 character TABLE and COLUMN names New support added for relationship cardinality ranges (for example, 1..5) New “Forward Engineering” wizard Ability to tag ATTRIBUTES/COLUMNS as PII Support for Hive VIEW Partitions
Erwin Data Modeler is offered as a native 64-bit application with access to sufficient memory to complete operations on large models (A 32-bit option is still available).
What is a Data Model and Data Modeler Responsibilities?
What’s in it: Data Model, High Level Data Modeler Responsibilities along with images of a conceptual data model, logical data model and physical Data Model is explained using Erwin Data Modeling Tool.
Video Tutorial 2:
Explain Data Modeling Development Life Cycle?
What’s in it: This question is asked by the Interviewers. Our video explains step by step process in Data Modeling Development Life Cycle. This life cycle is common for RDMS Data Modeling and Dimensional Data Modeling.
Video Tutorial 3:
What is an ER Diagram?
What’s in it: ER Diagram also know as Erwin Relationship Diagram is explained with a data model created by using Erwin Data Modeling Tool. Primary Key Constraint, Composite Primary Key Constraint, Foreign Key Constraint, Composite Foreign Key Constraint are explained here in this Data Modeling Video Tutorial.
Video Tutorial 4:
What is a Conceptual Data Model?
What’s in it: This is the first phase in designing the data model in the Data Modeling Development Life and is explained in Detail with image of Erwin Data Model.
Video Tutorial 5:
What is a Logical Data Model?
What’s in it: The is second phase in designing the data model in the Data Modeling Development Life Cycle and is explained in details
Video Tutorial 6:
What is the difference between a Logical Data Model and Physical Data Model?
What’s in it: The differences between Logical Data Model and Physical Data Model is tabulated and explained with the help of a data model created from the Erwin Tool.
Video Tutorial 7:
What is an Entity and Attribute?
What’s in it: Entity and Attribute are explained with a Diagram.
Video Tutorial 8:
What is Identifying and Non-Identifying Relationship?
What’s in it: Identifying and Non-Identifying Relationship are explained with the help of a small data model drawn from Erwin Data Modeling Tool. Difference between those two are also explained.
Video Tutorial 9:
What is Forward Engineering & What is Reverse Engineering?
What’s in it: Forward Engineering, Reverse Engineering, SuperType and SubType are explained.
Video Tutorial 10:
What is Data Model Meta Data & Data Model Repository
What’s in it: Data Model Meta Data & Data Model Repository are explained in this video tutorial.
Video Tutorial 11:
What is the process to create a Data WareHouse Schema and What are the steps involved in designing the data mart?
What’s in it: This video explains important points in designing the Data Mart and Data Warehouse Schema.
Video Tutorial 12:
What is Dimensional Data Model and a Star Schema?
What’s in it: This video explains the basics of Dimensional Data Model and Schema with OLA use case as the example.
Video Tutorial 13:
What is ETL? / What is Datawarehouse? / What is DataMart?
What’s in it: Basics of ETL, Datawarehouse and Datamart are explained in this Data Modeling Video Tutorial.
Video Tutorial 14:
What is Check Constraint? / What is a Sequence? / What is an Index?
What’s in it: Brief explanation of Check Constraint, Sequence, and Index is explained. Also NULL values in Unique constraint are explained. The above topic is an important question in the Data Modeling Interview..
Video Tutorial 15:
What is OLTP Data Modeling? / What are the different types of constraints? / What is an Unique Constraint?
What’s in it: Brief explanation about OLTP data modeling and constraint. This is an important question in Data Modeling Interview.
Video Tutorial 16:
What is a Foreign Key Constraint? / What is a composite Foreign Key constraint?
What’s in it: Foreign Key Constraint is explained in a detailed manner by taking an example from IBM.
Video Tutorial 17:
Erwin Data Modeling Interview Questions – Part 1
What’s in it:
This video helps with the list of interview questions that can be asked in creating : Conceptual data model by Erwin. Logical data model by Erwin. Physical data model by Erwin.
Video Tutorial 18:
Dimensional Data Modeling Interview Questions – Part 1
What’s in it:
These Dimensional Data Modeling Questions are related to Data Warehouse and Data Mart. When you work as an ETL developer or BI developer, these questions will be asked in the interview.
Exactly One, Zero or one, One or more, Zero/One/More, More than one
Relationship Cardinality:
One to One, One to Many, Many to Many
Optionality
Relationship Cardinality and Optionality Notations
How to read the relationships?
Not Null Constraint
7 – Relationships in an OLTP Data Model using Erwin
Introduction by the trainer and students
Introduction about data model
Use Case: H1B Applicant Data Model
Identifying lookup table and transaction tables
Creation of data model using Erwin
creation of entity and primary keys in Erwin
Creating conceptual data model
Identifying null and not null
Identifying cardinality
Identifying one to one, one to zero/one/many, one to one/many
Non identifying relationship
8 – Relationships in a Data Model using Erwin
Many to Many relationship
How to create a Conceptual Data Model
Identifying relationship
How to handle composite primary keys in a data model
Why data analysis is important?
Self-Referential Integrity Relationship
Cardinality
How to create a Logical Data Model
How to create a Lookup Script?
How to do forward engineering (schema generation)?
9 – SuperType, SubType
Generalization with subjoin subtypes (Mutually exclusive)
Attribute Inheritance
Disjoint (Exclusive) Constraint
Overlapping (Inclusive) Constraint
Participation (Completeness Constraint)
Specialization (Top Down Approach)
Generalization (Physical Data Model)
Super Type Implementation (Single Table)
Sub Type Implementation
When we should use supertype implementation?
When we should use subtype implementation?
10 – Normalization Concepts
Business Process: What happens in a clinic with doctors patients visiting fee and medicines provided?
Normalization Intro
What is Normalization? Why Normalization is required?
What is redundancy?
Insert, Update, Delete Anomaly
Data Analysis of a clinic (clinic, doctor, patient, fees and
medicines provided) – Case Study
Functional Dependency
1NF, 2NF, 3NF
11 – Normalization – Data Analysis of Student data (student, course, grade, instructor)-
Business Process: What happens in student, course, instructor relationship?
Create tables in 1 NF, 2NF, 3NF with the business rule “1 course can be taught by only one instructor”
How to modify the data model when business rules change “1 course can be taught by more than one instructor”
Normalization – Small Retail Sales Data – 1NF, 2NF, 3NF
Business Process: How to analyze retail sales data
Data Analysis of a small Retail Sales Data which consists of order, payment, shipment, federal tax, state tax, billing, items, items ordered, item name, total price, ordered quantity and how to handle multiple payment for an order
12 – UBER-OLA OLTP Data Model – Sample Case Study
Business Process: How to store Rider Information and how to query the data
OLTP:
How to build conceptual data model?
How to build source schema (OLTP)?
How to build target schema (Dimensional)?
How to aggregate the data on daily basis and monthly basis (olap analysis)?
How to calculate the daily trip cost?
How to find out the drivers who cancelled the trip?
How much money driver made?
How to run different queries on top of this data model?
Uber carpool scenario
Business Process: How to capture Training Center
Employee/Student/Course Information/fees/training session
How to capture the products that are explained?
How to capture the training videos that are sold?
how to implement identifying, non-identifying relationships?
How to implement super type and sub type?
14 – Cloud OLTP Data Model – Sample Case Study
Business Process: How to store the online sales for a product? –
Microsoft Office 365 as example from Web browser Application
Explanation of office 365 application
Explanation of table creation
How to capture users, plans, option and subscription
15 – How to create a Staffing OLTP Data Model? – Sample Case Study
Business Process: How to hire a candidate.
16 – US Banking OLTP Data Model – Sample Case Study
Business Process: How to store financial and nonfinancial
transactions for a Checking Account?
17 – US Mortgage OLTP Data Model
Business Process – How to create an OLTP Data Model for US Mortgage URLA 1003 Application Form?
18 – Dimensional Data Modeling:
Concepts:
What is Business Intelligence?
What is Data Warehouse?
What is Data Mart?
What is ETL Process?
Difference between OLTP and Dimensional
What is Inman’s Approach?
What is Kimball’s Approach?
What is Dependent Data Mart? And What is an Independent Data Mart?
What is Source Schema and What is Target Schema?
How to design the Data Mart?
What is Star Schema?
What is Snowflake Schema?
What is Business Process?
What is a grain statement and what is the lowest level of Granularity?
What is a Dimension?
What is a Degenerate Dimension?
What is a Causal Dimension?
What is Junk Dimension?
What is Outrigger Dimension?
What is Slowly Changing Dimension Type1, Type2, and Type3?
What is a Fact or a Measure?
What is Additive Fact, Semi Additive fact and Non-Additive Fact?
What is a Fact Table?
What is Fact less Fact Table?
What is Transaction Fact?
What is Aggregate Fact?
What is Accumulation Fact?
What is a Periodic Fact?
What is a surrogate key?
What is the specialty of Date Key as a surrogate column?
How to avoid NULL VALUES in the primary keys of a Fact Table?
19 – Dimensional Data Models – Case Study:
Point of Sales Data Model – How to design the star schema?
US Mortgage URLA 1003 Data Model
Retail Bank Data Model– How to store ATM Transactions?
OLA/Uber Data Model – How to store ride information?
Cloud Data Model – How to store products sold on cloud environment
Banking Data Model: How to store Daily and Monthly Data?
20 – Fundamentals:
How to use Erwin Data Modeling Tool, Oracle SQL Data Modeler, TOAD Data Modeler, SAP Power Designer.
SQL Server’s T-SQLTraining with Agile and Data Modeling
Online Training Start Date : 16th July, 2020
Course Start Date: Training will be provided as per your convenient time slots! Please call us at 91-9080157239 for more details!
Email: AntonysTrainingandSolution@gmail.com
Chapter 1: Introduction about Data, Column, Datatype, Record, PK, FK
How to install SQL Server Management Studio?
How to install SQL Server Express Edition?
What is a database?
How to Backup / Delete / Recover a SQL Server Database?
How to Export / Import Data from SQL server?
How to Detach / Attach a Database?
What is Server Login / Database User / Schema / Role / Privileges?
What is Data?
What is a column?
What is a datatype?
What is a record?
What is a table?
What is primary key?
What is composite primary key?
What is a foreign key?
What is composite foreign key?
What is a schema?
Chapter 2: Introduction to SDLC, Waterfall Methodology, Agile Methodology
Introduction to Software Development Life Cycle.
What is Waterfall methodology?
What is Agile methodology?
Scrum Model
What is Product Catalog?
What is Sprint Catalog?
What is Project Team?
Who is Product Owner?
Scrum Development Team
Scrum Master
What is Sprint Planning?
What is Daily Scrum?
What is Sprint Review?
What is Sprint Retrospective?
What is Product Backlog Refinement?
Chapter 3: Introduction to Database and Application:
What is a Server?
Introduction to SQL Databases
What is a Client?
What is an Application?
What is a Desktop Application?
What is a Browser Based Application?
What is a Mobile Based Application?
What is Client Server Architecture?
Chapter 4: Data Analysis:
Introduction to Data Analysis from RDBMS perspective
Introduction to Data Profiling from RDBMS perspective
Chapter 5: Introduction to SQL Server Environment:
Basic Features, Components and Tools
How to start and stop SQL Server Instances and Services
Introduction to Management Studio
Types of System Databases in SQL
How to create a database?
Chapter 6: Data Definition Language (DDL):
Datatype:
What is a datatype?
Different types of datatypes
Table:
How to Create / Alter / Drop Table (column, datatype)
How to truncate a Table?
Constraint:
How to Create / DROP NULL and NOT NULL?
How to Create / Drop Primary Keys and Composite Primary Keys?
How to Create / Drop Foreign key Constraints?
How to Create / Drop Unique Constraint and Composite Unique Constraint?
How to Create / Drop Check Constraints?
Chapter 7: Data Manipulation Language (DML):
How to insert, delete and update date in a table?
Chapter 8: Data Query Language (DQL):
What is ANSI SQL?
What is T-SQL?
How Select Statements are used in OLTP and OLAP environment:
How to frame a Select Statement on all columns?
How to frame a Select Statement on few columns?
What is WHERE clause? How to select all records and few records?
How to use different conditions in where clause?
How to sort and unsort the data?
How to use Boolean operators in where clause?
How to use Arithmetic operators in where clause?
How to use IN operator in where clause?
How to use comparison operator in where clause?
How to use NULL and NOT NULL in the where clause?
How to use predefined (default) functions?
How to use set operators like UNIION and Intersect?
How to use Mathematical Functions?
How to use Character Functions?
How to use Advanced Functions?
How to use Date Functions?
Group Functions:
What is Grouping the data? And where it will be useful?
How to use group function MIN, MAX, SUM, AVG, COUNT
What is HAVING clause?
How to combine GROUP by and HAVING?
Queries:
What is a Sub Query?
What is a Nested Query?
What is Inner Query?
What is Outer Query?
What is co-related Sub Query?
Joins:
Inner Join or Simple Join
Right Outer Join
Left Outer Join
Full Outer Join
Chapter 9: NOSQL Databases:
Introduction to NoSQL Databases
Chapter 10: Normalization and E/R Diagram through Oracle’s SQL Developer Data Modeler:
What is Normalization?
What is Denormalization?
How to analyze the requirement?
How to find out entities and relationships through Normalization Techniques (1NF, 2NF, 3NF)?
How to draw E-R (Entity Relationship Diagram)? – One to One, One to many, Many to Many, Self-Referential Integrity (Recursive), Cardinality and Optionality.
Chapter 11: About Data Model:
Explanation of a Logical Data Model
Explanation of a Physical Data Model
How ER data (Normalized Data) is converted into Tables?
Explanation of Dimensional Data Model
What is OLTP environment?
What is OLAP environment?
Chapter 12: Duties and Responsibilities of a SQL Developer:
What is Role?
What is Level?
What is a duty?
What is a responsibility?
What are the duties and responsibilities of a SQL Developer?
Entity Relationship Diagram (also called as ER Diagram, ER Model, ERD) contains entities/attributes and relationships with those entities. ER Model is a methodological approach to create entities in normalized forms to minimise redundancy. It is drawn with the use of Data Modeling Tools and the following steps are done to create the entity relationship diagram.
Understanding the business requirements
Meetings / discussions with stakeholders (BA/SME/PM etc) to find out entities and relationships
Data Modeler designs the ER diagram.
Data Modeling with ER Model:
In the above mentioned example,
1. Following entities are created by data modeler
Department
Gender
Employee
Salary Grade
Degree
2. Then the data modeler adds the relevant attributes to those entities.
3. Creating attributes: Example Employee
Employee ID
Department Number
Salary Grade Identifier
Gender Code
Degree Code
Employee Name
Birth DATE
4. The data modeler assigns relevant datatypes for each attribute based on the type of data stored:
Example Employee ID in employee entity
5. Relationships:
After creating entities and attributes the data modeler decides how to create the primary key, foreign key
Creating primary key:
Example: Employee ID in Employee entity
Creating foreign key:
Example: Employee entity references Department entity, Gender entity, Salary Grade and Degree Entity
Optionality and Cardinality options:
(Source: www.Erwin.com)
Creating foreign key:
Example: Employee entity references Department entity, Gender entity, Salary Grade and Degree Entity
In The below ER diagram created from Erwin Data Modeling Tool by using Information Engineering (IE) notation, near to that department entity, one can see ZERO and ONE and near employee entity, ZERO AND ONE AND MORE. These symbols have specific meaning and the data modeler has assigned the right symbols due to business rules.
Similarly, entities are created in ER diagram and the data modeler gets the approval from the business team, technical to release the data models.
Data Modeling Software Tools Trial Versions:
Oracle has released “SQL Developer Data Modeler” and it is a free data modeling tool. If you want to become a data modeler, you can start designing data with “SQL Developer Data Modeler”.
If you are interested to learn data modeling by using Erwin or SAP PowerDesigner or Oracle SQL Data Modeler, please reach us for more details – Training@learndatamodeling.com or 91-90801 57239.
In this section, you can view some of the Demo Videos that I have posted on the YouTube. You can find the Syllabus of the actual Data Modeling Video Tutorials here! If you are interested in buying this Video, please reach us at 91-9080157239 or you email us your requirements to AntonysTrainingandSolution@gmail.com.
01. Data Modeling Development Life Cycle
02. Data Warehouse Training – Table and PK
03. Simple Select Statement and Alter Statements
04. Data Warehouse Training ETL Tools
05. Demo Data Modeling and Data Warehouse Training Normalization
06 Demo Data Modeling and Data Warehouse Training – Cardinality and Optionality
