Learn to build a data warehousing solution with new AWS course

Kumar Kumaraguruparan

Did you know the data warehousing market was $13.4B USD by the end of 2020 and is growing at 7.6% (IDC)? If you’re a data warehouse engineer, a data platform engineer, or a solutions architect with the responsibility to build data analytics pipelines using Amazon Redshift, our new one-day, virtual classroom course, Building Data Analytics Solutions Using Amazon Redshift, will help you develop the skills needed to build a modern data architecture that includes Amazon Redshift. As the demand for data warehousing expertise is expected to increase in the next few years, consider expanding your cloud data warehousing skills with this training course.

What’s different about data warehousing today?

Data warehouses are key to modern data architectures that include machine learning (ML), relational databases, and a data lake. You may want to derive combined insights from data stored in a data warehouse, relational database, or data lake without unnecessary data movement; or, you may want to build an ML model based on the data in a data warehouse using familiar SQL commands. The SQL language is widely used and considered to be important skillset needed for working with data warehouses and data lakes (IDC study).

Amazon Redshift, a cloud data warehouse service, integrates with data lakes based on Amazon S3 and relational database services, such as Amazon Relational Database Service (Amazon RDS) for PostgreSQL, Amazon Aurora PostgreSQL-Compatible Edition, Amazon RDS for MySQL, and Amazon Aurora MySQL-Compatible Edition. It also supports building and using ML models using familiar SQL commands, thereby reducing the skills needed to take advantage of ML.

As data continues to grow exponentially, the cost-effective operation of a data warehouse becomes even more important. Amazon Redshift supports cost-effective operations by separating the scaling of storage from compute and maintains query performance with the help of features such as Advanced Query Acceleration (AQUA) and advanced workload management. In addition, Amazon Redshift uses ML-powered features to reduce the performance and maintenance burden on database administrators.

Developing the skills needed to take advantage of these capabilities is critical for organizations migrating from on-premises data warehouses to Amazon Redshift and for customers building cloud-native solutions with Amazon Redshift.

About the course

Building Data Analytics Solutions Using Amazon Redshift is an intermediate-level, one-day course that will show you how to build a data analytics pipeline using Amazon Redshift in an interactive environment with the help of expert AWS instructors. You’ll learn three major skills:

  1. How to leverage the separation of compute and storage;
  2. How to analyze all your data regardless of its location—a data warehouse, data lake, or relational database, such as Amazon Aurora; and
  3. How to leverage ML-powered automation to reduce maintenance burden.

The course starts with data ingestion and storage, progresses to transformation and analysis, and then covers security and Amazon Redshift cluster monitoring. You’ll learn to automate common configurations, such as distribution keys, sort keys, and workload management. AWS authorized instructors will use labs and interactive sessions to demonstrate data sharing between producer and consumer clusters and the use of the Amazon Redshift’s data API to programmatically access data. Finally, you’ll take part in an instructor-facilitated exercise to build a data analytics solution to solve a business problem.

To get the most out of this course, we recommend that learners have one or more years of data warehouse management experience and foundational knowledge of AWS. You can satisfy the foundational knowledge requirement by completing AWS Technical Essentials or Architecting on AWS, followed by Building Data Lakes on AWS.

Whether you attend the class virtually or in-person, you’ll have the opportunity to ask questions, work through solutions with your peers, and get real-time feedback from accredited AWS instructors with deep technical knowledge.

Is the AWS Certified Data Analytics – Specialty your goal?

If you want to earn an industry-recognized credential from AWS that validates your expertise in AWS Analytics services, you may want to consider the AWS Certified Data Analytics – Specialty certification. While the Building Data Analytics Solutions Using Amazon Redshift course explores data-warehouse-centered ingestion, storage, and processing topics, we offer additional information to help you prepare for the AWS Certified Data Analytics – Specialty exam.

Additional resources

If you’re interested in learning more about our AWS Training and Certification offerings for data analytics, download our AWS Data Analytics Ramp-Up Guide. We offer many free, on-demand digital resources as well as several virtual instructor-led courses for data analytics.

 

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