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Building Modern Data Analytics Solutions on AWS Course in Australia

Master modern data architectures with hands-on AWS tools

32 hours of expert-led training sessions

Four intermediate-level AWS course options to explore

Learn from AWS-certified instructors with real-world expertise

Access to expert-led lessons, labs, & case studies

Flexible learning options to fit your schedule & learning style

Various payment methods with instalment plans available

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Overview

What you will master with us:

  • Create & govern data lakes using AWS Lake Formation tools
  • Develop big data pipelines powered by Amazon EMR
  • Execute Spark-based batch analysis on EMR platforms
  • Analyze high-velocity data with Amazon Kinesis
  • Secure & enhance analytics on Redshift clusters
  • Apply AWS Glue to manage & scale storage needs
  • Design low-latency streaming systems with Amazon MSK

Upcoming sessions

Curriculum

1

Introduction to Data Lakes

2

Data ingestion, cataloging and preparation

3

Building a Data Lake with AWS Lake formation

4

Data processing and analysis

5

Additional Lake formation configurations

6

Modern data architecture

1

Overview of Data Analytics and the Data Pipeline

2

Introduction to Amazon EMR

3

Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage

4

High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR

5

Processing and Analysing Batch Data with Amazon EMR and Apache Hive

6

Serverless Data Processing

7

Security and Monitoring of Amazon EMR Clusters

8

Designing Batch Data Analytics Solutions

9

Developing Modern Data Architectures on AWS

1

Overview of Data Analytics and the Data Pipeline

2

Using Amazon Redshift in the Data Analytics Pipeline

3

Introduction to Amazon Redshift

4

Ingestion and Storage

5

Processing and Optimizing Data

6

Security and Monitoring of Amazon Redshift Clusters

7

Designing Data Warehouse Analytics Solutions

8

Developing Modern Data Architectures on AWS

1

Overview of Data Analytics and the Data Pipeline

2

Using Streaming Services in the Data Analytics Pipeline

3

Introduction to AWS Streaming Services

4

Using Amazon Kinesis for Real-time Data Analytics

5

Securing, Monitoring and Optimizing Amazon Kinesis

6

Using Amazon MSK in Streaming Data Analytics Solutions

7

Securing, Monitoring and Optimizing Amazon MSK

8

Designing Streaming Data Analytics Solutions

9

Developing Modern Data Architectures on AWS

Meet your Trainer

Our Trainers

Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.

We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.

Our Trainers

Learning Outcomes

After you complete this training, you will be able to:

  • 1

    Master the setup of well-governed cloud-based data lakes using AWS Lake Formation

  • 2

    Create high-performing analytics pipelines with the powerful features of Amazon EMR

  • 3

    Attain practical experience with Apache Spark to process batch data workloads

  • 4

    Develop real-time analytics applications using Amazon Kinesis for fast data streaming

  • 5

    Build scalable data warehouses using Amazon Redshift’s modern architecture

  • 6

    Use AWS Glue to streamline, secure, and manage your ETL and storage pipelines

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    Prerequisites

    To enroll in the Building Modern Data Analytics Solutions on AWS course in Australia, we recommend that you fulfil these eligibility requirements:

    • Understanding of relational databases and data warehousing basics
    • Previous experience with data analytics tools and techniques
    • Hands-on knowledge of core AWS services like S3, EC2, and IAM
    • Basic skills in scripting languages, such as Python
    • Familiarity with ETL (Extract, Transform, Load) workflows and data preparation techniques
    • Knowing the basics of networking, including VPC, subnets, and security groups

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    Frequently asked questions

    This Building Modern Data Analytics Solutions on AWS course in Australia is designed to teach professionals how to create full-scale data analytics pipelines using AWS. You get hands-on experience with tools like Amazon EMR, Redshift, Glue, Kinesis, Lake Formation, and MSK. You also explore modern data architectures and work with both batch and live data workflows.

    Professionals learn and practice several tools in this course, like -

    • Amazon Lake Formation
    • AWS Glue and EMR
    • Apache Spark
    • Amazon Redshift
    • Amazon Kinesis and MSK

    The following are the minimum eligibility requirements to enrol in this course -

    • Basic understanding of relational databases and data warehousing
    • Experience with data analytics tools and techniques
    • Familiarity with AWS services like S3, EC2, and IAM
    • Scripting knowledge
    • Understanding of ETL workflows and data preparation
    • Basic networking concepts like VPCs, subnets, and security groups

    This Building Modern Data Analytics Solutions on AWS Training in Australia is ideal for professionals like -

    • Data engineers
    • Cloud architects
    • Developers
    • Analysts
    • IT professionals

    The course curriculum is divided into four modules covering the following major topics -

    • Building Data Lakes on AWS
    • Building Batch Data Analytics Solutions on AWS
    • Building Data Analytics Solutions using Amazon Redshift
    • Building Streaming Data Analytics Solutions on AWS

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