Building Modern Data Analytics Solutions on AWS Course in Rwanda
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
4.9/54.9/5Overview
What our training includes:
- Set up & maintain data lakes efficiently with AWS Lake Formation
- Create data analytics workflows using Amazon EMR
- Perform batch analytics through Apache Spark on EMR clusters
- Process live data streams using Amazon Kinesis
- Strengthen data security & performance in Redshift analytics
- Leverage AWS Glue for flexible & scalable data storage
- Build real-time streaming architectures with Amazon MSK
Upcoming sessions
Curriculum
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
Overview of Data Analytics and the Data Pipeline
Introduction to Amazon EMR
Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage
High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR
Processing and Analysing Batch Data with Amazon EMR and Apache Hive
Serverless Data Processing
Security and Monitoring of Amazon EMR Clusters
Designing Batch Data Analytics Solutions
Developing Modern Data Architectures on AWS
Overview of Data Analytics and the Data Pipeline
Using Amazon Redshift in the Data Analytics Pipeline
Introduction to Amazon Redshift
Ingestion and Storage
Processing and Optimizing Data
Security and Monitoring of Amazon Redshift Clusters
Designing Data Warehouse Analytics Solutions
Developing Modern Data Architectures on AWS
Overview of Data Analytics and the Data Pipeline
Using Streaming Services in the Data Analytics Pipeline
Introduction to AWS Streaming Services
Using Amazon Kinesis for Real-time Data Analytics
Securing, Monitoring and Optimizing Amazon Kinesis
Using Amazon MSK in Streaming Data Analytics Solutions
Securing, Monitoring and Optimizing Amazon MSK
Designing Streaming Data Analytics Solutions
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.
Learning Outcomes
After you complete this training, you will be able to:
1
Learn to create scalable & secure cloud data lakes using AWS Lake Formation’s governance features
2
Build efficient analytics pipelines that handle large datasets with Amazon EMR
3
Use Apache Spark for fast, batch data processing across distributed systems
4
Set up real-time streaming analytics using the capabilities of Amazon Kinesis
5
Design secure & scalable data warehouses with Amazon Redshift’s advanced tools
6
Manage ETL workflows & data storage efficiently using AWS Glue services
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
To enrol in the Building Modern Data Analytics Solutions on AWS Course in Rwanda, 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, & 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, & security groups
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Frequently asked questions
This Building Modern Data Analytics Solutions on AWS course is all about teaching 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.
This course covers several important tools, like -
- Amazon Lake Formation
- AWS Glue and EMR
- Apache Spark
- Amazon Redshift
- Amazon Kinesis and MSK
Our training is available in several different modes for convenient learning. These include -
- Instructor-led group sessions
- Personalized one-on-one training
- Live interactive online classes
The major topics covered in this course are -
- 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
This Building Modern Data Analytics Solutions on AWS Training in Rwanda includes hands-on exposure to:
- Amazon Kinesis for real-time analytics
- Amazon MSK for scalable data streaming
- Monitoring and security practices for both Kinesis and MSK
- Design of complete streaming analytics pipelines
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