Drive Team Excellence with AWS Data Warehousing Corporate Training

Empower your teams with expert-led on-site/in-house or virtual/online AWS Data Warehousing Training through Edstellar, a premier corporate training company for organizations globally. Our tailored AWS Data Warehousing corporate training course equips your employees with the skills, knowledge, and cutting-edge tools needed for success. Designed to meet your specific needs, this AWS Data Warehousing group training program ensures your team is primed to drive your business goals. Transform your workforce into a beacon of productivity and efficiency.

AWS Data Warehousing refers to storing, managing, and analyzing large volumes of structured and unstructured data using cloud-based services provided by Amazon Web Services (AWS). It is vital for organizations as it enables the centralized storage and analysis of data from various sources and allows them to scale their data capabilities cost-effectively, gaining faster insights to drive informed decisions. The training provides professionals with essential skills to leverage AWS services effectively for designing and optimizing data warehousing solutions.

Edstellar’s AWS Data Warehousing course offers onsite/virtual training sessions to ensure a comprehensive learning experience. The course provides professionals with practical experience and real-world scenarios, ensuring they develop the skills necessary to excel. Edstellar's AWS Data Warehousing training courses empower professionals to apply their knowledge effectively within their organizations, driving innovation and success in data management and analysis.

Key Skills Employees Gain from AWS Data Warehousing Training

AWS Data Warehousing skills corporate training will enable teams to effectively apply their learnings at work.

  • SQL Query Optimization
  • Database Schema Design
  • Workload Management
  • Cluster Performance Monitoring
  • Dashboard Visualization
  • ETL (Extract, Transform, Load)

Key Learning Outcomes of AWS Data Warehousing Training

Edstellar’s AWS Data Warehousing training for employees will not only help your teams to acquire fundamental skills but also attain invaluable learning outcomes, enhancing their proficiency and enabling application of knowledge in a professional environment. By completing our AWS Data Warehousing workshop, teams will to master essential AWS Data Warehousing and also focus on introducing key concepts and principles related to AWS Data Warehousing at work.


Employees who complete AWS Data Warehousing training will be able to:

  • Craft complex SQL queries and analyze query execution plans for optimization
  • Design efficient database schemas to enhance query performance and storage utilization
  • Configuring workload management parameters and balancing query concurrency effectively
  • Monitor cluster performance metrics, enabling audit logging and implementing backup strategies
  • Create insightful dashboards with Amazon QuickSight to visualize key performance indicators and trends
  • Extract, transform, and load data from diverse sources, such as Amazon S3, DynamoDB, and EMR, into Amazon Redshift

Key Benefits of the AWS Data Warehousing Corporate Training

Attending our AWS Data Warehousing classes tailored for corporations offers numerous advantages. Through our on-site/in-house or virtual/online AWS Data Warehousing training classes, participants will gain confidence and comprehensive insights, enhance their skills, and gain a deeper understanding of AWS Data Warehousing.

  • Learn advanced data warehousing techniques and best practices tailored to the organization's needs
  • Develop a deep understanding of AWS data warehousing services and how to leverage them effectively
  • Expand the professional's knowledge of data integration, ETL processes, and query optimization strategies
  • Equip teams with practical skills to design, implement, and manage robust data warehousing solutions on AWS
  • Access resources and support to stay updated with the latest trends and advancements in AWS data warehousing technologies

Topics and Outline of AWS Data Warehousing Training

Our virtual and on-premise AWS Data Warehousing training curriculum is divided into multiple modules designed by industry experts. This AWS Data Warehousing training for organizations provides an interactive learning experience focused on the dynamic demands of the field, making it relevant and practical.

  1. Relational databases
    • Database model overview
    • Entity-relationship model
  2. Data warehousing concepts
    • Data aggregation
    • Dimensional modeling
    • Fact and dimension tables
    • ETL process overview
  3. The intersection of data warehousing and big data
    • Big data technologies overview
    • Scalability challenges
    • Integration with the Hadoop ecosystem
    • Data lake architectures
  4. Overview of data management in AWS
    • AWS database services overview
    • AWS Glue for ETL
    • Data lakes on Amazon S3
    • Redshift Spectrum for data analytics
  5. Hands-on lab 1: Introduction to Amazon Redshift
    • Setting up an AWS account
    • Accessing AWS console
    • Basic Redshift cluster creation
  1. Conceptual overview
    • Architecture components
    • Data distribution concepts
  2. Real-world use cases
    • Retail analytics
    • Financial reporting
    • IoT data analytics
    • Social media analytics
  3. Hands-on lab 2: Launching an Amazon Redshift cluster
    • Configuring Redshift cluster
    • Security group configuration
    • Cluster launch process
    • Basic query execution in Redshift
  1. Building the cluster
    • Cluster configuration options
    • Node types and sizes
    • Multi-node vs single-node clusters
    • Cluster security considerations
  2. Connecting to the cluster
    • Connection methods
    • Client tools setup
    • JDBC/ODBC configuration
    • Query optimization techniques
  3. Controlling access
    • IAM roles and policies
    • Database user management
    • Access control lists (ACLs)
    • Encryption options
  4. Database security
    • Data encryption at rest and in transit
    • Network security best practices
  5. Load data
    • ETL processes
    • Data loading strategies
    • Data migration tools
    • Data validation and integrity checks
  6. Hands-on lab 3: Optimizing database schemas
    • Schema design best practices
    • Table distribution methods
    • Compression techniques
    • Performance tuning considerations
  1. Schemas and data types
    • Redshift data types overview
    • Choosing appropriate data types
  2. Columnar compression
    • Compression algorithms
    • Storage optimization techniques
  3. Data distribution styles
    • Key distribution styles
    • Data skew and distribution considerations
    • Distribution key selection best practices
    • Comparison of distribution styles
  4. Data sorting methods
    • Sort key selection strategies
    • Choosing between compound and interleaved sort keys
  1. Data sources overview
    • Overview of AWS data sources
    • Data integration challenges
  2. Amazon S3
    • Using S3 as a data lake
    • Data ingestion methods into S3
    • S3 security and access controls
  3. Amazon DynamoDB
    • NoSQL data modeling concepts
    • Integrating DynamoDB with Redshift
    • Streaming data from DynamoDB to Redshift
  4. Amazon EMR
    • Overview of EMR services
    • Integrating EMR with Redshift
  5. Amazon Kinesis Data Firehose
    • Real-time data streaming concepts
    • Firehose integration with Redshift
  6. AWS Lambda Database Loader for Amazon Redshift
    • Lambda function configuration
    • Data loading with Lambda
    • Error handling and monitoring
    • Lambda security considerations
  7. Hands-on lab 4: Loading real-time data into an Amazon Redshift database
    • Real-time data pipeline setup
    • Integration with Kinesis Data Firehose
    • Redshift data loading process
    • Data transformation and enrichment techniques
  1. Preparing data
    • Data cleansing techniques
    • Data transformation best practices
  2. Loading data using COPY
    • COPY command syntax overview
    • Using COPY with different data formats
  3. Maintaining tables
    • Vacuum and analyze operations
    • Table reorganization strategies
  4. Concurrent write operations
    • Managing concurrent writes efficiently
  5. Troubleshooting load issues
    • Error handling techniques
    • Log analysis
    • Performance tuning
    • Load monitoring and alerting
  6. Hands-on lab 5: Loading data with the COPY command
    • COPY command execution
    • Monitoring load progress
    • Troubleshooting load errors
    • Performance optimization techniques
  1. Amazon Redshift SQL
    • Basic SQL queries
    • Redshift-specific SQL features
  2. User-defined functions (UDFs)
    • Creating and using UDFs in Redshift
    • Performance considerations for UDFs
  3. Factors that affect query performance
    • Data distribution impact
    • Query optimization techniques
  4. The EXPLAIN command and query plans
    • Understanding query plans
    • Optimizing query performance using EXPLAIN
  5. Workload management (WLM)
    • WLM configuration options
    • Query queuing and prioritization
    • WLM best practices
    • Performance tuning with WLM
  6. Hands-on lab 6: Configuring workload management
    • WLM configuration setup
    • Query queuing and prioritization
    • WLM performance monitoring
    • WLM query execution analysis
  1. Amazon Redshift Spectrum
    • Spectrum architecture overview
    • External tables creation
  2. Configuring data for Amazon Redshift Spectrum
    • Data partitioning best practices
    • Choosing optimal file formats
  3. Amazon Redshift Spectrum queries
    • Query optimization techniques for Spectrum
  4. Hands-on lab 7: Using Amazon Redshift Spectrum
    • Configuring Spectrum access
    • Querying external data with Spectrum
    • Spectrum performance optimization
    • Cost management with Spectrum
  1. Audit logging
    • Enabling audit logging
    • Analyzing audit logs
  2. Performance monitoring
    • Monitoring cluster performance metrics
    • Setting up performance alerts
  3. Events and notifications
    • Configuring event notifications
    • Handling event notifications
  4. Resizing clusters
    • Vertical and horizontal scaling options
  5. Backing up and restoring clusters
    • Creating and restoring cluster snapshots
    • Disaster recovery strategies
  6. Resource tagging and limits and constraints
    • Tagging resources for tracking and management
    • Setting resource limits and constraints
  7. Hands-on lab 8: Auditing and monitoring clusters
    • Setting up cluster monitoring
    • Analyzing cluster performance metrics
    • Configuring event notifications
    • Handling critical events
  1. Power of visualizations
    • Importance of data visualization in decision-making
    • Key principles of effective data visualization
  2. Building dashboards
    • Dashboard design best practices
    • Tools for building interactive dashboards
  3. Amazon QuickSight editions and features
    • Overview of QuickSight editions
    • Key features of Amazon QuickSight

Target Audience for AWS Data Warehousing Training Course

The AWS Data Warehousing training course is ideal for database architects, database administrators, database developers, data analysts, data warehouse developers, ETL (Extract, Transform, Load) developers, data scientists, and data integration specialists.

The AWS Data Warehousing training program can also be taken by professionals at various levels in the organization.

  • AWS Data Warehousing training for managers
  • AWS Data Warehousing training for staff
  • AWS Data Warehousing training for leaders
  • AWS Data Warehousing training for executives
  • AWS Data Warehousing training for workers
  • AWS Data Warehousing training for businesses
  • AWS Data Warehousing training for beginners
  • AWS Data Warehousing group training
  • AWS Data Warehousing training for teams
  • AWS Data Warehousing short course

Prerequisites for AWS Data Warehousing Training

Professionals with a basic understanding of relational databases, SQL queries, data modeling, ETL processes, cloud computing concepts, and familiarity with the Amazon Web Services (AWS) platform can take up the AWS Data Warehousing training course.

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Corporate Training Delivery Modes
for AWS Data Warehousing Training

At Edstellar, we understand the importance of impactful and engaging training for employees. To ensure the training is more interactive, we offer Face-to-Face onsite/in-house or virtual/online for companies. This approach has proven to be effective, outcome-oriented, and produces a well-rounded training experience for your teams.

 Virtual trainig

Our virtual training sessions bring expert-led, high-quality training to your teams anywhere, ensuring consistency and seamless integration into their schedules.

With global reach, your employees can get trained from various locations
The consistent training quality ensures uniform learning outcomes
Participants can attend training in their own space without the need for traveling
Organizations can scale learning by accommodating large groups of participants
Interactive tools can be used to enhance learning engagement
 On-site trainig

Edstellar's onsite training delivers immersive and insightful learning experiences right in the comfort of your office.

Higher engagement and better learning experience through face-to-face interaction
Workplace environment can be tailored to learning requirements
Team collaboration and knowledge sharing improves training effectiveness
Demonstration of processes for hands-on learning and better understanding
Participants can get their doubts clarified and gain valuable insights through direct interaction
 Off-site trainig

Edstellar's off-site training programs offer a unique opportunity for teams to immerse themselves in focused and dynamic learning environments away from their usual workplace distractions.

Distraction-free environment improves learning engagement
Team bonding can be improved through activities
Dedicated schedule for training away from office set up can improve learning effectiveness
Boosts employee morale and reflects organization's commitment to employee development
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Course Completion Certificate

Upon successful completion of the AWS Data Warehousing training course offered by Edstellar, employees receive a course completion certificate, symbolizing their dedication to ongoing learning and professional development.

This certificate validates the employee's acquired skills and is a powerful motivator, inspiring them to enhance their expertise further and contribute effectively to organizational success.

Course Completion Certificate

Meet Our Elite Trainers

The instructor-led training is conducted by certified trainers with extensive expertise in the field. Participants will benefit from the instructor's vast knowledge, gaining valuable insights and practical skills essential for success in Access practices.

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