Do you NEED an insight into your stored data?

AWS have launched 3 short duration (1-day, In-person or virtual Instructor Led Training (vILT)) courses to upskill data engineers using AWS cloud so as to be able to develop business insights from their multi-siloed data stores. These 3 independent courses replace the longer three-day Big Data course.
We recommend that you start your learning experience with the Building Data Lakes on AWS before taking any of the other associated courses.

1. Building Data Lakes on AWS - In this 1-day course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalogue, and Amazon Athena to analyse data. The course lectures and labs further your learning with the exploration of several common data lake architectures.
   Our ideal candidate recommendation: One year of experience building data analytics pipelines or have completed the Data Analytics Fundamentals course (Digital course).
   
   
2. Building Batch Data Analytics Solutions on AWS - In this 1-day course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloguing, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR
   Our ideal candidate recommendation: One year of experience managing open-source data frameworks such as Apache Spark or Apache Hadoop and completion of Building Data Lakes on AWS (vILT) or Getting Started with AWS Glue (Digital course). You may also wish to refresh your knowledge with the AWS Hadoop Fundamentals course (Digital course).
   
   
   
3. Building Data Analytics Solutions using Amazon RedShift - In this 1-day course, you will build a data analytics solution using Amazon Redshift, a cloud data warehouse service. The course focuses on the data collection, ingestion, cataloguing, storage, and processing components of the analytics pipeline. You will learn to integrate Amazon Redshift with a data lake to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon Redshift.
   Our ideal candidate recommendation: One-year experience managing data warehouses and completion of Building Data Lakes on AWS (vILT course)

Course combinations: If you are using, or planning to use, Amazon EMR (Elastic Map Reduce) then the Building Batch Data Analytics Solutions on AWS is highly recommended. If you are using, or planning to use, Amazon Redshift then the Building Data Analytics Solutions using Amazon Redshift is the course for you.

You may not have thought about the concept of Data Analytics, but in this day and age – understanding the data you already have could give your organisation a significant competitive edge. Reach out to us if this is something you may be interested in, or if you have a business need those analytics may help solve.

Calvin Riskowitz is a Champion AWS Authorised Instructor (AAI)