DATABASE AND DATA WAREHOUSE ONLINE TRAINING

Batch type:  Weekdays/Weekends

Mode of Training:  Classroom/Online/Corporate Training

Highly Experienced Certified Trainer with 10+ yrs Exp. in Industry

Database Training Curriculum

Module 1: Introduction to Databases

Introduction to databases and their importance

Types of databases: relational, NoSQL, NewSQL

Understanding database management systems (DBMS)

Benefits and challenges of using databases

?Module 2: Relational Database Concepts

Entity-Relationship (ER) modeling

Tables, rows, columns, keys, and constraints

SQL fundamentals: querying, filtering, sorting

JOIN operations and relationships

Module 3: Database Design and Normalization

Functional dependency and normalization

Normal forms (1NF to 3NF)

Dealing with anomalies and redundancy

Denormalization and trade-offs

Module 4: Database Administration and Security

User roles and permissions

Backup, recovery, and maintenance

Data integrity and validation

Security best practices and encryption

Module 5: Advanced Database Concepts

Indexing and query optimization

Transactions and concurrency control

Triggers, stored procedures, and functions

Database performance tuning

Data Warehouse Training Curriculum:

Module 1: Introduction to Data Warehousing

What is a data warehouse?

Data warehouse architecture and components

Differences between operational databases and data warehouses

Benefits and challenges of data warehousing

Module 2: Data Modeling for Data Warehouses

Dimensional modeling and star schema

Fact tables and dimension tables

Snowflake schema and galaxy schema

Slowly Changing Dimensions (SCD) types

Module 3: ETL (Extract, Transform, Load) Processes

Extracting data from source systems

Data transformation and cleansing

Loading data into the data warehouse

ETL tools and best practices

Module 4: Data Warehouse Design Patterns

Kimball vs. Inmon methodologies

Hybrid approaches and best fit for different scenarios

Aggregations and pre-calculated measures

Managing historical data and time dimensions

Module 5: Data Warehouse Querying and Reporting

Introduction to Online Analytical Processing (OLAP)

Building multidimensional cubes

Query optimization techniques

Data visualization and reporting tools

Module 6: Data Warehouse Administration and Performance

Monitoring and managing data warehouse performance

Partitioning and indexing strategies

Handling large data volumes and scalability

Backup, recovery, and disaster planning

Module 7: Advanced Topics in Data Warehousing

Real-time data warehousing

Data lakes and data warehouse integration

Big data and unstructured data in data warehousing

Cloud-based data warehousing solutions

Capstone Project:

Participants work on a hands-on project that involves designing, building, and populating a data warehouse from scratch, implementing ETL processes, creating reports, and optimizing queries for performance.

DATABASE AND DATA WAREHOUSE ONLINE TRAINING

Batch type:  Weekdays/Weekends

Mode of Training:  Classroom/Online/Corporate Training

Highly Experienced Certified Trainer with 10+ yrs Exp. in Industry

Database Training Curriculum

Module 1: Introduction to Databases

Introduction to databases and their importance

Types of databases: relational, NoSQL, NewSQL

Understanding database management systems (DBMS)

Benefits and challenges of using databases

Module 2: Relational Database Concepts

Entity-Relationship (ER) modeling

Tables, rows, columns, keys, and constraints

SQL fundamentals: querying, filtering, sorting

JOIN operations and relationships

Module 3: Database Design and Normalization

Functional dependency and normalization

Normal forms (1NF to 3NF)

Dealing with anomalies and redundancy

Denormalization and trade-offs

Module 4: Database Administration and Security

User roles and permissions

Backup, recovery, and maintenance

Data integrity and validation

Security best practices and encryption

Module 5: Advanced Database Concepts

Indexing and query optimization

Transactions and concurrency control

Triggers, stored procedures, and functions

Database performance tuning

DATABASE AND DATA WAREHOUSE ONLINE TRAINING

Batch type:  Weekdays/Weekends

Mode of Training:  Classroom/Online/Corporate Training

Highly Experienced Certified Trainer with 10+ yrs Exp. in Industry

Database Training Curriculum

Module 1: Introduction to Databases

Introduction to databases and their importance

Types of databases: relational, NoSQL, NewSQL

Understanding database management systems (DBMS)

Benefits and challenges of using databases

Module 2: Relational Database Concepts

Entity-Relationship (ER) modeling

Tables, rows, columns, keys, and constraints

SQL fundamentals: querying, filtering, sorting

JOIN operations and relationships

Module 3: Database Design and Normalization

Functional dependency and normalization

Normal forms (1NF to 3NF)

Dealing with anomalies and redundancy

Denormalization and trade-offs

Module 4: Database Administration and Security

User roles and permissions

Backup, recovery, and maintenance

Data integrity and validation

Security best practices and encryption

Module 5: Advanced Database Concepts

Indexing and query optimization

Transactions and concurrency control

Triggers, stored procedures, and functions

Database performance tuning

Data Warehouse Training Curriculum:

Module 1: Introduction to Data Warehousing

What is a data warehouse?

Data warehouse architecture and components

Differences between operational databases and data warehouses

Benefits and challenges of data warehousing

Module 2: Data Modeling for Data Warehouses

Dimensional modeling and star schema

Fact tables and dimension tables

Snowflake schema and galaxy schema

Slowly Changing Dimensions (SCD) types

DATABASE AND DATA WAREHOUSE ONLINE TRAINING

Batch type:  Weekdays/Weekends

Mode of Training:  Classroom/Online/Corporate Training

Highly Experienced Certified Trainer with 10+ yrs Exp. in Industry

Database Training Curriculum

Module 1: Introduction to Databases

Introduction to databases and their importance

Types of databases: relational, NoSQL, NewSQL

Understanding database management systems (DBMS)

Benefits and challenges of using databases

Module 2: Relational Database Concepts

Entity-Relationship (ER) modeling

Tables, rows, columns, keys, and constraints

SQL fundamentals: querying, filtering, sorting

JOIN operations and relationships

Module 3: Database Design and Normalization

Functional dependency and normalization

Normal forms (1NF to 3NF)

Dealing with anomalies and redundancy

Denormalization and trade-offs

Module 4: Database Administration and Security

User roles and permissions

Backup, recovery, and maintenance

Data integrity and validation

Security best practices and encryption

Module 5: Advanced Database Concepts

Indexing and query optimization

Transactions and concurrency control

Triggers, stored procedures, and functions

Database performance tuning

Data Warehouse Training Curriculum:

Module 1: Introduction to Data Warehousing

What is a data warehouse?

Data warehouse architecture and components

Differences between operational databases and data warehouses

Benefits and challenges of data warehousing

Module 2: Data Modeling for Data Warehouses

Dimensional modeling and star schema

Fact tables and dimension tables

Snowflake schema and galaxy schema

Slowly Changing Dimensions (SCD) types

Module 3: ETL (Extract, Transform, Load) Processes

Extracting data from source systems

Data transformation and cleansing

Loading data into the data warehouse

ETL tools and best practices

Module 4: Data Warehouse Design Patterns

Kimball vs. Inmon methodologies

Hybrid approaches and best fit for different scenarios

Aggregations and pre-calculated measures

Managing historical data and time dimensions

DATABASE AND DATA WAREHOUSE ONLINE TRAINING

Batch type:  Weekdays/Weekends

Mode of Training:  Classroom/Online/Corporate Training

Highly Experienced Certified Trainer with 10+ yrs Exp. in Industry

Database Training Curriculum

Module 1: Introduction to Databases

Introduction to databases and their importance

Types of databases: relational, NoSQL, NewSQL

Understanding database management systems (DBMS)

Benefits and challenges of using databases

Module 2: Relational Database Concepts

Entity-Relationship (ER) modeling

Tables, rows, columns, keys, and constraints

SQL fundamentals: querying, filtering, sorting

JOIN operations and relationships

Module 3: Database Design and Normalization

Functional dependency and normalization

Normal forms (1NF to 3NF)

Dealing with anomalies and redundancy

Denormalization and trade-offs

Module 4: Database Administration and Security

User roles and permissions

Backup, recovery, and maintenance

Data integrity and validation

Security best practices and encryption

Module 5: Advanced Database Concepts

Indexing and query optimization

Transactions and concurrency control

Triggers, stored procedures, and functions

Database performance tuning

Data Warehouse Training Curriculum:

Module 1: Introduction to Data Warehousing

What is a data warehouse?

Data warehouse architecture and components

Differences between operational databases and data warehouses

Benefits and challenges of data warehousing

Module 2: Data Modeling for Data Warehouses

Dimensional modeling and star schema

Fact tables and dimension tables

Snowflake schema and galaxy schema

Slowly Changing Dimensions (SCD) types

Module 3: ETL (Extract, Transform, Load) Processes

Extracting data from source systems

Data transformation and cleansing

Loading data into the data warehouse

ETL tools and best practices

Module 4: Data Warehouse Design Patterns

Kimball vs. Inmon methodologies

Hybrid approaches and best fit for different scenarios

Aggregations and pre-calculated measures

Managing historical data and time dimensions

Module 5: Data Warehouse Querying and Reporting

Introduction to Online Analytical Processing (OLAP)

Building multidimensional cubes

Query optimization techniques

Data visualization and reporting tools

Module 6: Data Warehouse Administration and Performance

Monitoring and managing data warehouse performance

Partitioning and indexing strategies

Handling large data volumes and scalability

Backup, recovery, and disaster planning

DATABASE AND DATA WAREHOUSE ONLINE TRAINING

Batch type:  Weekdays/Weekends

Mode of Training:  Classroom/Online/Corporate Training

Highly Experienced Certified Trainer with 10+ yrs Exp. in Industry

Database Training Curriculum

Module 1: Introduction to Databases

Introduction to databases and their importance

Types of databases: relational, NoSQL, NewSQL

Understanding database management systems (DBMS)

Benefits and challenges of using databases

Module 2: Relational Database Concepts

Entity-Relationship (ER) modeling

Tables, rows, columns, keys, and constraints

SQL fundamentals: querying, filtering, sorting

JOIN operations and relationships

Module 3: Database Design and Normalization

Functional dependency and normalization

Normal forms (1NF to 3NF)

Dealing with anomalies and redundancy

Denormalization and trade-offs

Module 4: Database Administration and Security

User roles and permissions

Backup, recovery, and maintenance

Data integrity and validation

Security best practices and encryption

Module 5: Advanced Database Concepts

Indexing and query optimization

Transactions and concurrency control

Triggers, stored procedures, and functions

Database performance tuning

Data Warehouse Training Curriculum:

Module 1: Introduction to Data Warehousing

What is a data warehouse?

Data warehouse architecture and components

Differences between operational databases and data warehouses

Benefits and challenges of data warehousing

Module 2: Data Modeling for Data Warehouses

Dimensional modeling and star schema

Fact tables and dimension tables

Snowflake schema and galaxy schema

Slowly Changing Dimensions (SCD) types

Module 3: ETL (Extract, Transform, Load) Processes

Extracting data from source systems

Data transformation and cleansing

Loading data into the data warehouse

ETL tools and best practices

Module 4: Data Warehouse Design Patterns

Kimball vs. Inmon methodologies

Hybrid approaches and best fit for different scenarios

Aggregations and pre-calculated measures

Managing historical data and time dimensions

Module 5: Data Warehouse Querying and Reporting

Introduction to Online Analytical Processing (OLAP)

Building multidimensional cubes

Query optimization techniques

Data visualization and reporting tools

Module 6: Data Warehouse Administration and Performance

Monitoring and managing data warehouse performance

Partitioning and indexing strategies

Handling large data volumes and scalability

Backup, recovery, and disaster planning

Module 7: Advanced Topics in Data Warehousing

Real-time data warehousing

Data lakes and data warehouse integration

Big data and unstructured data in data warehousing

Cloud-based data warehousing solutions

Capstone Project:

Participants work on a hands-on project that involves designing, building, and populating a data warehouse from scratch, implementing ETL processes, creating reports, and optimizing queries for performance.

DATABASE AND DATA WAREHOUSE ONLINE TRAINING

Batch type:  Weekdays/Weekends

Mode of Training:  Classroom/Online/Corporate Training

Highly Experienced Certified Trainer with 10+ yrs Exp. in Industry

Database Training Curriculum

Module 1: Introduction to Databases

Introduction to databases and their importance

Types of databases: relational, NoSQL, NewSQL

Understanding database management systems (DBMS)

Benefits and challenges of using databases

Module 2: Relational Database Concepts

Entity-Relationship (ER) modeling

Tables, rows, columns, keys, and constraints

SQL fundamentals: querying, filtering, sorting

JOIN operations and relationships

Module 3: Database Design and Normalization

Functional dependency and normalization

Normal forms (1NF to 3NF)

Dealing with anomalies and redundancy

Denormalization and trade-offs

Module 4: Database Administration and Security

User roles and permissions

Backup, recovery, and maintenance

Data integrity and validation

Security best practices and encryption

Module 5: Advanced Database Concepts

Indexing and query optimization

Transactions and concurrency control

Triggers, stored procedures, and functions

Database performance tuning

Data Warehouse Training Curriculum:

Module 1: Introduction to Data Warehousing

What is a data warehouse?

Data warehouse architecture and components

Differences between operational databases and data warehouses

Benefits and challenges of data warehousing

Module 2: Data Modeling for Data Warehouses

Dimensional modeling and star schema

Fact tables and dimension tables

Snowflake schema and galaxy schema

Slowly Changing Dimensions (SCD) types

Module 3: ETL (Extract, Transform, Load) Processes

Extracting data from source systems

Data transformation and cleansing

Loading data into the data warehouse

ETL tools and best practices

Module 4: Data Warehouse Design Patterns

Kimball vs. Inmon methodologies

Hybrid approaches and best fit for different scenarios

Aggregations and pre-calculated measures

Managing historical data and time dimensions

Module 5: Data Warehouse Querying and Reporting

Introduction to Online Analytical Processing (OLAP)

Building multidimensional cubes

Query optimization techniques

Data visualization and reporting tools

Module 6: Data Warehouse Administration and Performance

Monitoring and managing data warehouse performance

Partitioning and indexing strategies

Handling large data volumes and scalability

Backup, recovery, and disaster planning

Module 7: Advanced Topics in Data Warehousing

Real-time data warehousing

Data lakes and data warehouse integration

Big data and unstructured data in data warehousing

Cloud-based data warehousing solutions

Capstone Project:

Participants work on a hands-on project that involves designing, building, and populating a data warehouse from scratch, implementing ETL processes, creating reports, and optimizing queries for performance.

DATABASE AND DATA WAREHOUSE ONLINE TRAINING

Batch type:  Weekdays/Weekends

Mode of Training:  Classroom/Online/Corporate Training

Highly Experienced Certified Trainer with 10+ yrs Exp. in Industry

Database Training Curriculum

Module 1: Introduction to Databases

Introduction to databases and their importance

Types of databases: relational, NoSQL, NewSQL

Understanding database management systems (DBMS)

Benefits and challenges of using databases

Module 2: Relational Database Concepts

Entity-Relationship (ER) modeling

Tables, rows, columns, keys, and constraints

SQL fundamentals: querying, filtering, sorting

JOIN operations and relationships

Module 3: Database Design and Normalization

Functional dependency and normalization

Normal forms (1NF to 3NF)

Dealing with anomalies and redundancy

Denormalization and trade-offs

Module 4: Database Administration and Security

User roles and permissions

Backup, recovery, and maintenance

Data integrity and validation

Security best practices and encryption

Module 5: Advanced Database Concepts

Indexing and query optimization

Transactions and concurrency control

Triggers, stored procedures, and functions

Database performance tuning

Data Warehouse Training Curriculum:

Module 1: Introduction to Data Warehousing

What is a data warehouse?

Data warehouse architecture and components

Differences between operational databases and data warehouses

Benefits and challenges of data warehousing

Module 2: Data Modeling for Data Warehouses

Dimensional modeling and star schema

Fact tables and dimension tables

Snowflake schema and galaxy schema

Slowly Changing Dimensions (SCD) types

Module 3: ETL (Extract, Transform, Load) Processes

Extracting data from source systems

Data transformation and cleansing

Loading data into the data warehouse

ETL tools and best practices

Module 4: Data Warehouse Design Patterns

Kimball vs. Inmon methodologies

Hybrid approaches and best fit for different scenarios

Aggregations and pre-calculated measures

Managing historical data and time dimensions

Module 5: Data Warehouse Querying and Reporting

Introduction to Online Analytical Processing (OLAP)

Building multidimensional cubes

Query optimization techniques

Data visualization and reporting tools

Module 6: Data Warehouse Administration and Performance

Monitoring and managing data warehouse performance

Partitioning and indexing strategies

Handling large data volumes and scalability

Backup, recovery, and disaster planning

Module 7: Advanced Topics in Data Warehousing

Real-time data warehousing

Data lakes and data warehouse integration

Big data and unstructured data in data warehousing

Cloud-based data warehousing solutions

Capstone Project:

Participants work on a hands-on project that involves designing, building, and populating a data warehouse from scratch, implementing ETL processes, creating reports, and optimizing queries for performance.