Building Data Lakes on AWS Course in Bahrain
Intermediate-level training from AWS
7 specialised modules with real-time projects
Use AWS Lake Formation to build a data lake
Learn with course lectures & hands-on labs
Gain access to high-quality study materials
Expert-guided preparation with mock exams
Hassle-free payment options & flexible training available
4.9/56925 EnrolledEnrolled Learners
4.9/56925 EnrolledEnrolled Learners
Overview
What we’re going to teach you:
- Understand the essential elements that make up a data lake
- Discover typical architectural patterns for data lake solutions
- Handle large-scale data sets with AWS Lake Formation
- Create detailed data catalogs via AWS Glue crawlers
- Execute data queries on lakes using Amazon Athena
- Implement detailed permissions & tag-driven access controls
- Organize & structure data efficiently using AWS Glue
Upcoming sessions
Curriculum
1
Describe the value of data lakes
2
Compare data lakes and data warehouses
3
Describe the components of a data lake
4
Recognize common architectures built on data lakes
1
Describe the relationship between data lake storage and data ingestion
2
Describe AWS Glue crawlers and how they are used to create a data catalog
3
Identify data formatting, partitioning and compression for efficient storage and query
1
Recognize how data processing applies to a data lake
2
Use AWS Glue to process data within a data lake
3
Describe how to use Amazon Athena to analyze data in a data lake
4
Lab 01: Building a Data Lake with AWS Lake Formation
1
Describe the features and benefits of AWS Lake Formation
2
Use AWS Lake Formation to create a data lake
3
Understand the AWS Lake Formation security model
4
Lab 2: Build a data lake using AWS Lake Formation
1
Explain the available built-in Blueprints to create and populate a new Lake Formation
2
Describe methods for applying advanced permissions to secure data access and workflow
3
Describe fine-grained row/cell access control
4
Explain the Lake Formation Tag-based access control mechanism and the different use cases for Named access control vs. Tag-based access control
5
Describe access flow that enforces fine-grained access policies to both catalog metadata and underlying data resource for analytics services connecting to Lake Formation
1
Explain capabilities of a modern data architecture: Scalable data lakes, Purpose-build analytics services, Seamless data movement, unified governance and performance and cost-effectiveness
2
Articulate the typical data movement within a modern data architecture: Inside out, Outside in, Around the perimeter and Sharing across
3
Describe focus of building and maintaining data products as a service
4
Describe a typical Data Mesh architecture using Lake Formation and the key enablers supporting this methodology
5
Lab 3: Building and publishing a data product in Lake Formation
1
Post course knowledge check
2
Architecture review
3
Course review
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.
Learning Outcomes
After finishing the course, you will be able to:
1
Understand the importance and advantages of building data lakes
2
Differentiate between data lakes & traditional data warehouses
3
Utilize AWS Glue crawlers for creating structured data catalogs
4
Conduct data analysis within data lakes using Amazon Athena
5
Construct secure & scalable data lakes leveraging AWS Lake Formation
6
Implement granular access controls using Lake Formation features
7
Develop & share data products via Lake Formation tools
Learners Point Certificate
Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.
Prerequisites
Before enrolling in the Building Data Lakes on AWS in Bahrain, the eligibility requirements are as follows:
- Completed the AWS Technical Essentials classroom course
- One year of experience building data analytics pipelines or have completed the Data Analytics Fundamentals digital course
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Frequently asked questions
The Building Data Lakes on AWS Course in Bahrain is an intermediate-level course meant for professionals with basic cloud and data experience. Our program offers practical lab activities to help professionals build and manage scalable data lakes using Amazon Web Services (AWS).
These AWS Data Lakes are centralized repositories for storing large volumes of both structured and unstructured data. You will learn to use AWS services such as AWS Glue, Amazon Athena and AWS Lake Formation.
Building a data lake on AWS involves using a combination of storage, cataloging, transformation, security and analytics tools. These services work together to help you ingest, organise and query large volumes of structured and unstructured data. These key AWS tools include:
- Amazon S3 – Central storage layer for raw and curated datasets
- AWS Glue – For metadata cataloging and running ETL (Extract, Transform, Load) jobs
- AWS Lake Formation – Simplifies setup, governance and fine-grained access control of data lakes
- Amazon Athena – Enables serverless SQL queries directly on S3 data
- Amazon Redshift Spectrum – Extends Redshift queries to access data in S3 without loading
- AWS Kinesis – Handles streaming data ingestion from real-time sources
- AWS Lambda – Automates event-driven data transformations and processing
Yes, our course in Bahrain highlights essential best practices to design and manage scalable data lakes on AWS. These practices ensure your data architecture supports growing workloads, maintains performance and stays cost-efficient over time. Some of the best practices covered in this training are:
- Using Amazon S3 as the data lake foundation for durability, elasticity and virtually unlimited scalability
- Partitioning and compressing datasets to improve query performance and reduce storage costs
- Implementing schema evolution for flexible handling of structured and unstructured data
- Applying fine-grained security controls with AWS Lake Formation, IAM roles and encryption
- Automating ETL workflows using AWS Glue and Lambda for consistent and repeatable data transformations
The AWS Data Lake Training in Bahrain helps professionals with practical skills to design, build and manage modern cloud-based data solutions. By mastering AWS-native tools, you’ll gain the ability to handle large datasets, implement security and enable analytics that drive smarter business decisions. Several key benefits for professionals include:
- Grasp fundamental Data Lake principles
- Construct scalable and secure Data Lakes
- Simplify data ingestion and cataloging processes
- Develop effective data transformation workflows
- Utilise serverless tools for data querying
- Maintain strong data security and adhere to compliance standards
- Adopt AWS recommended practices
This AWS Data Lake course follows a course curriculum with the following 6 course modules. These modules contain all the major topics about building data lakes using AWS services. The six important modules are as follows:
- Introduction to data lakes
- Data ingestion, cataloging, and preparation
- Building a Data Lake with AWS Lake Formation
- Data Processing and Analysis
- Additional Lake Formation configurations
- Modern Data Architecture Course Wrap Up
Yes, professionals have access to our Data Lakes on AWS training from locations outside Bahrain. It is available in locations across multiple GCC regions. We offer in-depth training globally, which helps students to gain this important certification. These locations are:
Yes, our training in Bahrain includes practical strategies to optimise costs while building and managing AWS data lakes. You will learn how to balance performance, scalability and expenses using AWS-native features and best practices. Covered cost optimisation practices include:
1. Using Amazon S3 storage classes for cost-effective data storage
2. Applying lifecycle policies to move or delete unused data
3. Optimising queries in Athena through partitioning and data compression
4. Utilising spot instances and serverless services to minimise compute expenses
5. Monitoring with AWS Cost Explorer and CloudWatch to track and control usage
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