Data warehousing certification training

Data warehousing certification training
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A Self-Paced course designed to give you a head start into Data warehousing and train you on different concepts of Data warehousing along with the implementations of these concepts.


Learning Objectives - Discussing the basic concepts of a data warehouse and why it is needed. Difference between an operating system and an analytical system, Datamarts. Approaches to building a data warehouse.

Topics - 
1. What is a data warehouse? - Definition and explanation of the four terms - subject oriented, integrated, non-volatile and time variant

2. Need for a data warehouse 3. Difference between a database and a data warehouse. OLTP and OLAP? 4. Datamart - The smaller cousin of the data warehouse

5. ODS - Operational Data Store - Definition and explanation of 4 terms - Subject-oriented, Integrated, Current, Volatile, Detailed

6. Benefits of ODS 7. Design approach - Top-down approach, bottom-up approach, Federated

Learning Objectives - Learning what a dimension and a fact are, the different types of dimensions and facts. Reporting the concept of Hierarchy.

Topics -
1. Dimensions and facts - What are the dimensions and facts?

2. Types of dimensions - emphasis on SCD 1,2,3 implementations 3. Types of facts 4. What are hierarchies - Types of Hierarchies

Learning Objectives - Organizing data in multiple tables. Understanding normalization and its different forms. Learning what is a schema and the different types of schemas along with metadata.

Topics -
1. Normalization

2. Schemas - What is a schema. Types - Star, Snowflake, Galaxy 3. The significant role of metadata

Learning Objectives - Understanding principles of requirement gathering to build a warehouse and dimensional modeling.

Topics -
1. Requirement gathering

2. Principles of dimensional modeling

3. Modeling - ER diagrams

Learning Objectives - Understanding where will the data come from and how will the data come and Populating the warehouse. Learning concepts of Extracting data, Transforming data and Loading the data into different tables.

Topics -
1. ETL Concept - Architectural components - like Source, Staging, Atomic, Dimension

2. Transformation - Data Validation, Data Accuracy, Data Type Conversion, Business Rule Application

3. Data Loading techniques.

Learning Objectives - Implementing a data warehouse Project.

Topics - Discuss a project, its problem statement, probable solutions, and implement one solution.

Learning Objectives - Discussing the basic concepts of a data warehouse and why it is needed. Difference between an operating system and an analytical system, Datamarts. Approaches to building a data warehouse.

Topics - 
1. What is a data warehouse? - Definition and explanation of the four terms - subject oriented, integrated, non-volatile and time variant

2. Need for a data warehouse 3. Difference between a database and a data warehouse. OLTP and OLAP? 4. Datamart - The smaller cousin of the data warehouse

5. ODS - Operational Data Store - Definition and explanation of 4 terms - Subject-oriented, Integrated, Current, Volatile, Detailed

6. Benefits of ODS 7. Design approach - Top-down approach, bottom-up approach, Federated

Learning Objectives - Learning what a dimension and a fact are, the different types of dimensions and facts. Reporting the concept of Hierarchy.

Topics -
1. Dimensions and facts - What are the dimensions and facts?

2. Types of dimensions - emphasis on SCD 1,2,3 implementations 3. Types of facts 4. What are hierarchies - Types of Hierarchies

Learning Objectives - Organizing data in multiple tables. Understanding normalization and its different forms. Learning what is a schema and the different types of schemas along with metadata.

Topics -
1. Normalization

2. Schemas - What is a schema. Types - Star, Snowflake, Galaxy 3. The significant role of metadata

Learning Objectives - Understanding principles of requirement gathering to build a warehouse and dimensional modeling.

Topics -
1. Requirement gathering

2. Principles of dimensional modeling

3. Modeling - ER diagrams

Learning Objectives - Understanding where will the data come from and how will the data come and Populating the warehouse. Learning concepts of Extracting data, Transforming data and Loading the data into different tables.

Topics -
1. ETL Concept - Architectural components - like Source, Staging, Atomic, Dimension

2. Transformation - Data Validation, Data Accuracy, Data Type Conversion, Business Rule Application

3. Data Loading techniques.

Learning Objectives - Implementing a data warehouse Project.

Topics - Discuss a project, its problem statement, probable solutions, and implement one solution.

This Data warehousing course enables participants with concepts of Data warehousing like Facts, Schema, Metadata, Normalization, Data transformation, Dimensional Modeling, and ETL Concepts.

After the completion of Data warehousing course at ProICT Training, you will be able to: 

1. Understand the concept and need of Data warehouse 

2. Implement concepts of dimension and fact table 

3. Implement data modeling, normalization and schema concepts 4. Model a Data warehouse 

5. Implement ETL jobs

This course is a foundation for anyone who aspires to become a Data warehouse Architect, a Data warehouse Developer or a Data warehouse Business Analyst in the field of Data warehousing and Business Intelligence. The following professionals can go for this course : 

1. BI /ETL Professionals

2. Project Managers 

3. Testing Professionals 

4. Mainframe Professionals 

5. Analytics Professionals 

6. Software Developers and Architects

The pre-requisites for this course includes the basic understanding of Databases.

As we move from intuition-based decision making to factual decision making, it is increasingly important to capture data and store it in a way that allows us to make smarter decisions. This is where Data warehouse comes into the picture. There is a huge demand for Data warehousing professionals and this course acts as a foundation which opens the door to a variety of opportunities in Business Intelligence space.

For your practical work, we will help you setup ProICT's Virtual Machine in your System. The required installation guide is present in LMS.
As soon as you enrol into the course, your LMS (The Learning Management System) access will be functional. You will immediately get access to our course content in the form of a complete set of Videos, PPTs, PDFs and Assignments. You can start learning right away.
Yes! Soon after enrolling you have lifetime access to the course materials.
ProICT is the largest online education company and lots of recruitment firms contacts us for our students profiles from time to time. Since there is a big demand for this skill, we help our certified students get connected to prospective employers. We also help our customers prepare their resumes, work on real life projects and provide assistance for interview preparation. Having said that, please understand that we don't guarantee any placements however if you go through the course diligently and complete the project you will have a very good hands on experience to work on a Live project.
The pre-requisites for this course include basic knowledge of SQL, General Relational Database (Oracle), Microsoft Windows GUI, Basic Unix, Windows Command line. 
You can pay by Credit Card, Debit Card or NetBanking from all the leading banks. We use a CCAvenue Payment Gateway. For USD payment, you can pay by Paypal. We also have EMI options available.
 
 
You no longer need a credit history or a credit card to purchase this course. Using ZestMoney, we allow you to complete your payment with a EMI plan that best suits you. It's a simple 3 step procedure:
  • Fill your profile: Complete your profile with Aadhaar, PAN and employment details.
  • Verify your account: Get your account verified using netbanking, ekyc or uploading documents
  • Activate your loan: Setup automatic repayment using NACH to activate your loan