Data Warehousing on AWS Training

Data Warehouse helps in gathering and analysis the historical data, which helps in analyse the business growth.

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Duration: 3 Days

Course fee:$599.00 (₹0)

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Product Description

Data Warehouse is the collection of tools which is used to help in analyze the large volume of advanced data. It means Data Warehouse is the database kept separate from the functional database. The reason behind to keep Data Warehouse separate is to keep smooth function of the database record. Because the operational database is for particular task and Data Warehouse has complex queries and present a general form of data. Data warehouse has no frequent data updation but it relates to historical data which helps organisations in analysis their business. Data Warehouse also used in organize the database which helps user to analyze and take important decisions. Data Warehouse provides Online Analytical Processing (OLAP) tools which helps in better analysis of data in a multidimensional space. Now a days Data warehouse becoming the important platform for data analysis and analytical processing.

Objectives

  • Determine The Relationship between other Big Data Systems and Amazon Redshift.
  • Use BI Tool to perform Data Visualization and Data Analysis.
  • Procedures and approach for data warehouses design.
  • Identify Data Sources and Requirements.
  • Write queries to boost the performance.

Advantages of Data Warehousing on AWS Training

  • Load millions of rows in seconds.
  • It allows you to automate the common task to manage and monitor your data.
  • You can easily resize your cluster based on your capacity and performance.

Target Audience

  • Dbase Architects
  • Dbase Administrators
  • Dbase developers
  • Data analysts and scientists

Prerequisites

  • Knowledge of database design and relational databases concepts.

Additional Information

Day 1

1. Basic Introduction to Amazon Web Services (AWS)

2. Understanding the concept of Data Warehousing

3. Introduction to Amazon Redshift

4. Overview on the Components of Amazon Redshift

5. Understanding the Modern Analytics for Warehousing

6. Architecture Concept for Data Warehousing

Day 2

1. Dealing with Various Data Warehousing Technological Options

2. Understanding the Amazon RedShift Advanced Terminologies

3. Concept of using Tools for Database Migrations

4. Approaches of the Data Warehousing

5. Recognising source of data and requirements

6. Data Warehouse Design

7. Data Loading into Warehouse

Day 3

1. Queries Writing and Performance Tuning

2. Data Warehouse maintenance

3. Data analysis and visualization

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