Surveys from IDC, NewVantage Partners, and a report by Global Knowledge have revealed the facts regarding an accelerating rate at which data is growing, a slow rate of adoption of modern data-driven culture, and a big cause of such a slow response while responding to the acceleration which is not the data but lack of right amount of talent with data analytics and database skills.
Migrating to AWS Cloud for the need of data analytics to handle such an explosion of data while delivering performance, optimizing cost, ease of use, breaking the silos, leveraging security and governance, maintaining audits, adopting managed and serverless services and leveraging rich integrations brings the motivation to upskill the existing workforce and to attract the desired newcomers.
But how to quickly upskill employees on AWS for Analytics and Database needs?
AWS offers well-defined courses that give an actionable way for working professionals to build required data analytics and database skills, helping organizations quickly achieve momentum in consulting business.
- Cloud Migration
- AIML & IoT
Let us break it into stages – Just Map as per your requirement!
- Stage 1: Breaking the legacy and ready to be a cloud-native
- Course 1: Break Free of Legacy Databases
Why and how to break the legacy and move the databases to AWS Cloud-Native Databases.
- Course 2: AWS Database Offerings
Overview of AWS Purpose-Built Databases.
- Course 3: Introduction to Database Migration
How to migrate databases to AWS Cloud using AWS Database Migration Service and AWS Schema Conversion Tool
- Stage 2: Adoption of Fully Managed Services on AWS
- Course 1: Moving to Managed Databases on AWS
Journey from Self-Managed Database Solutions to Fully Managed AWS Purpose-Built Databases
- Course 2: Planning and Designing Databases on AWS
Deep dive into reasons behind having so many AWS Purpose-Built Databases while covering Relational and NoSQL Databases in-depth with proper use cases and hands-on
Strategies for migrations
- Stage 3: Modernizing Data Warehouse
As the name suggests, it is about best practices, which always come in handy.
How Amazon Redshift participates in Data Analytics Solutions on AWS with a handsome overview of the service itself, and of course, the lab’s part is just AWSome!
How Amazon EMR can be used to handle batch processing with its capabilities.
- Stage 4: Building Modern Applications with Purpose-Built Databases
Modern Applications Demand Purpose-Built Databases.
- Course 2: Developing with Amazon DynamoDB
How modern applications interact with Amazon DynamoDB.
A hands-on approach to how DynamoDB can participate in serverless architectures
- Stage 5: Bringing valuable insights out of data
- Course 1: Building Data Lakes on AWS
How to leverage AWS Data Analytics services to build data lakes on AWS
- Course 2: Visualizing with Amazon QuickSight
A quick introduction to cater to the need for the visualization phase of the data analytics pipeline using Amazon QuickSight
Handling ML (Machine Learning) using Amazon SageMaker
A good mix of well-curated, purpose-built on-demand courses and instructor-led courses offered by AWS can drastically change the game for working professionals, all capable of embedding the skills needed for today’s data-driven culture.
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CloudThat is an official AWS (Amazon Web Services) Advanced Consulting Partner and Training partner, AWS Migration Partner, AWS Data and Analytics Partner, AWS DevOps Competency Partner, Amazon QuickSight Service Delivery Partner, Amazon EKS Service Delivery Partner, and Microsoft Gold Partner, helping people develop knowledge of the cloud and help their businesses aim for higher goals using best-in-industry cloud computing practices and expertise. We are on a mission to build a robust cloud computing ecosystem by disseminating knowledge on technological intricacies within the cloud space. Our blogs, webinars, case studies, and white papers enable all the stakeholders in the cloud computing sphere.
WRITTEN BY Muhammad Imran