Basics
DML Vs DDL Operations
SQL Vs PL SQL
RDBMS Vs NoSQL
This program is well structured to provide you or your team with a broad understanding of cloud computing on Microsoft Azure Platform. Students can learn various data platform technologies that are available on Azure, and how they can take advantage of this technology to an organization’s benefit. The Training program also includes and is not limited to modules with which students can dive deep and understand Azure technologies that analyze text and images and relational, nonrelational, or streaming data.
Students who complete this training program successfully will become project-ready to create Azure services such as building pipelines with Azure Data Factory, running jobs on Azure Databricks, U-SQL with Azure SQL Database, etc. This training program will also describe the features of Azure AD and several methods of integrating it into an organization.
Students will as well learn at a high level how to identify and meet the data requirements to design data solutions that use Azure data services, design tasks that include designing Azure data storage solutions that use relational and non-relational data stores, batch and real-time data processing solutions, and data security and compliance solutions.
DATABASE CONCEPTS
Basics DML Vs DDL Operations SQL Vs PL SQL RDBMS Vs NoSQL Basic database objects
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SQL
Select Statements Restricting and Sorting data Single row functions Aggregating Using Group functions Manipulating Data Creating and Managing Tables Joins Including Constraints Using SET Operators Datetime Functions Subqueries |
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PLSQL
Declaring Variables Writing executable statements Writing control structures Composite data types Cursors Creating Procedures Creating Functions Managing Subprograms Creating Packages Creating Triggers |
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DBA FUNDAMENTALS
Managing Tables Managing Indexes Managing Data Integrity Managing Privileges Managing Users Managing Roles |
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DATABASE OBJECTS
Schema Objects Vs Non Schema Objects |
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SCHEMA OBJECTS
Clusters Constraints Database links Index-organized tables Indexes Materialized views Sequences Stored functions, stored procedures Synonyms Tables Views
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NON SCHEMA OBJECTS
Roles Rollback segments Tablespaces Users
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OTHER IMPORTANT TOPICS
Database Structures Relationships Data Integrity rules Data Normalization and Denormalization ER diagram Introduction to NoSQL and Unstructured Data |
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DATA WAREHOUSING CONCEPTS
What is a Data Warehouse? Data warehouse Vs OLTP System Data warehouse Vs OLTP System Bottom up approach EDW Vs Data Marts Typical Data Warehouse Architecture Logical Vs Physical Design Star Schema Snowflake Schema Staging area Data Marts Cardinality and Relationships Facts Dimensions Date Dimension Conformed Dimensions Shared Dimension The need for Materialized Views DWH Performance Tuning |
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ETL OVERVIEW
Extraction Transformation Loading and Refreshing Load time and Throughput Load scheduling Data Load Administration and Monitoring Lookups and Other important transformations Time Series analysis & Slowly Changing Dimension(SCD) ETL Tool Walkthrough (Informatica or Talend)
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OLAP
Symantec Layer Data Visualization Pivoting Functions Aggregations Cubes Multi-dimensional analysis Reports Data Rendering Performance tuning Slicing and Dicing Temporary tables Report automation and scheduling OLAP Tool walkthrough (Tableau or PowerBI) |
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TEST MANAGEMENT
Test Plan Test cases & scenarios Testing cycle UTC Integration Testing System testing UAT |
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TOOLS
HP ALM - High level –Theory Jira - High level demo |
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AGILE
Agile overview Agile types Agile methodologies Agile methodology in testing |
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UNIX
Unix Basics UNIX commands for various operations UNIX file I/O operations and file permissions |
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PROJECT WORK
Project involving creation of database objects, ER diagrams, Dimensional Modeling, ETL transformations, Mappings, and OLAP reports |
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