Corporate AWS Data Warehousing Training Course

Edstellar’s instructor-led AWS Data Warehousing training courses provide guidance on launching Amazon Redshift clusters, architecting data warehouses, and optimizing query performance. Upskill professionals to gain experience with AWS services such as Amazon DynamoDB, EMR, Kinesis, and S3 to contribute to robust data warehousing solutions.

24 - 32 hrs
Instructor-led (On-site/Virtual)
Language
English
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AWS Data Warehousing Training
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AWS Data Warehousing Corporate Training Course

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Drive Team Excellence with AWS Data Warehousing Training for Employees

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 Warehousingcorporate 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)

AWS Data Warehousing Training for Employees: Key Learning Outcomes

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

AWS Data Warehousing Training Topics and Outline

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

This Corporate Training for AWS Data Warehousing is ideal for:

What Sets Us Apart?

AWS Data Warehousing Corporate Training Prices

Our AWS Data Warehousing training for enterprise teams is tailored to your specific upskilling needs. Explore transparent pricing options that fit your training budget, whether you're training a small group or a large team. Discover more about our AWS Data Warehousing training cost and take the first step toward maximizing your team's potential.

Small Group
Large Groups

Request for a quote to know about our AWS Data Warehousing corporate training cost and plan the training initiative for your teams. Our cost-effective AWS Data Warehousing training pricing ensures you receive the highest value on your investment.

Request for a Quote

Our customized corporate training packages offer various benefits. Maximize your organization's training budget and save big on your AWS Data Warehousing training by choosing one of our training packages. This option is best suited for organizations with multiple training requirements. Our training packages are a cost-effective way to scale up your workforce skill transformation efforts..

Starter Package

125 licenses

64 hours of training (includes VILT/In-person On-site)

Tailored for SMBs

Most Popular
Growth Package

350 licenses

160 hours of training (includes VILT/In-person On-site)

Ideal for growing SMBs

Enterprise Package

900 licenses

400 hours of training (includes VILT/In-person On-site)

Designed for large corporations

Custom Package

Unlimited licenses

Unlimited duration

Designed for large corporations

View Corporate Training Packages

AWS Data Warehousing 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 employees' acquired skills and serves as a powerful motivator, inspiring them to further enhance their expertise and contribute effectively to organizational success.

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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Bringing you the Best AWS Data Warehousing Trainers in the Industry

The instructor-led AWS Data Warehousing 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 AWS Data Warehousing Access practices.

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Training Delivery Modes for AWS Data Warehousing Group 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 AWS Data Warehousing training for companies. This method has proven to be the most effective, outcome-oriented and well-rounded training experience to get the best training results for your teams.

Virtuval
Virtual

Instructor-led Training

Engaging and flexible online sessions delivered live, allowing professionals to connect, learn, and grow from anywhere in the world.

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On-Site
On-Site

Instructor-led Training

Customized, face-to-face learning experiences held at your organization's location, tailored to meet your team's unique needs and objectives.

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Off-Site
Off-site

Instructor-led Training

Interactive workshops and seminars conducted at external venues, offering immersive learning away from the workplace to foster team building and focus.

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