Building Data Lakes on AWS Course in Ethiopia
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
Pay with easy instalments
Flexible training available
4.85/55498 EnrolledEnrolled Learners
4.85/55498 EnrolledEnrolled Learners
Overview
What our training includes:
- Identify the fundamental components that make up a data lake
- Learn typical architectural patterns for data lake solutions
- Utilise AWS Glue to quickly collect and arrange data
- Create detailed data catalogues via AWS Glue crawlers
- Process large-scale data sets with AWS Lake Formation
- Use Amazon Athena to run data queries on lakes
- Set up detailed permissions and tag-driven access controls
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
Upon course completion, you’ll be able to:
1
Grasp the significance and benefits of developing data lakes
2
Distinguish between data lakes and traditional data warehouses
3
Use AWS Glue crawlers to build structured data catalogues
4
Perform data analysis in data lakes using Amazon Athena
5
Develop secure & scalable data lakes with AWS Lake Formation
6
Apply detailed access controls using Lake Formation capabilities
7
Design and distribute data products through 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 Ethiopia, 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
Building Data Lakes on AWS in Ethiopia is an intermediate-level training program which helps professionals with practical skills needed to build and manage scalable data lakes using Amazon Web Services (AWS). In this program, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data.
Through our Data Lake training, you will learn several essential AWS services. Some of these are:
1. Amazon S3
2. AWS Glue
3. Lake Formation
4. Amazon Athena
AWS Lake Formation is one of the essential AWS services which deals with Data Lake management. You will learn about it in the Building Data Lakes on AWS training in Ethiopia. It is used to simplify the process of setting up, securing and managing a data lake. It also helps to automate data ingestion and manage metadata.
If you enrol in our course in Data Lake in Ethiopia, you will gain numerous technical and analytical skills that are highly valued in today’s data-driven industries. These skills are as follows:
1. Data Lake architecture and design
2. AWS data services proficiency
3. Data ingestion and cataloguing skills
4. Data preparation and transformation
5. Data querying and analytical skills
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