Building Batch Data Analytics Solutions on AWS Course in Ethiopia
Design batch data analytics solutions using Amazon EMR & Spark
8 hours of course duration
Includes nine extensive & well-structured modules
Grasp in-demand skills for data engineering roles
Receive guided sessions from expert instructors
Learn through practice labs and interactive demos
Easy-to-fit weekend sessions for your hectic calendar
Convenient payment options with monthly instalments
4.9/55825 EnrolledEnrolled Learners
4.9/55825 EnrolledEnrolled Learners
Overview
What you will master with us:
- Develop large-scale batch data processing solutions with Amazon EMR
- Explore data ingestion methods using tools like Apache Hive and HBase
- Optimise data storage and management within Amazon EMR clusters
- Work with Apache Spark on EMR to analyse massive datasets
- Use Apache Hive to process and transform batch data workflows
- Get experience building machine learning models with EMR Notebooks
- Implement key security practices to protect Amazon EMR cluster environments
Upcoming sessions
Curriculum
1
Data analytics use cases
2
Using the data pipeline for analytics
1
Using Amazon EMR in analytics solutions
2
Amazon EMR cluster architecture
3
Interactive Demo 1: Launching an Amazon EMR cluster
4
Cost management strategies
1
Storage optimization with Amazon EMR
2
Data ingestion techniques
1
Apache Spark on Amazon EMR use cases
2
Why Apache Spark on Amazon EMR
3
Spark concepts
4
Interactive Demo 2: Connect to an EMR cluster and perform Scala commands using the Spark shell
5
Transformation, processing, and analytics
6
Using notebooks with Amazon EMR
7
Practice Lab 1: Low-latency data analytics using Apache Spark on Amazon EMR
1
Using Amazon EMR with Hive to process batch data
2
Transformation, processing, and analytics
3
Practice Lab 2: Batch data processing using Amazon EMR with Hive
4
Introduction to Apache HBase on Amazon EMR
1
Serverless data processing, transformation, and analytics
2
Using AWS Glue with Amazon EMR workloads
3
Practice Lab 3: Orchestrate data processing in Spark using AWS Step Functions
1
Securing EMR clusters
2
Interactive Demo 3: Client-side encryption with EMRFS
3
Monitoring and troubleshooting Amazon EMR clusters
4
Demo: Reviewing Apache Spark cluster history
1
Batch data analytics use cases
2
Activity: Designing a batch data analytics workflow
1
Modern data architectures
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 completion of this course, you will be able to:
1
Gain expertise in designing and implementing batch data analytics solutions using Amazon EMR and Apache Spark
2
Use AWS Step Functions to coordinate and automate complex data processing workflows
3
Follow best practices to enhance security, performance and cost-efficiency within EMR environments
4
Integrate tools like Apache Hive, HBase and AWS Glue for smooth and scalable data processing operations
5
Improve storage efficiency and cluster performance in Amazon EMR to deliver cost-optimised solutions
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 Batch Data Analytics Solutions on AWS Course in Ethiopia, candidates must fulfil these eligibility requirements:
- A minimum of one year of experience in managing open-source data frameworks such as Apache Spark or Apache Hadoop
- Completed either AWS Technical Essentials or Architecting on AWS
- Completed either Building Data Lakes on AWS or Getting Started with AWS Glue
Overall ratings by our students
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Frequently asked questions
With the help of our Building Batch Data Analytics Solutions on AWS Course in Ethiopia, professionals will learn how to design, develop, and oversee scalable batch data processing solutions using a variety of Amazon Web Services (AWS) tools. We concentrate on using automated, scheduled, and event-driven processing workflows to turn raw data into data insights.
Once you finish, you'll be suitably equipped for roles like:
- Data Engineer
- Cloud Solutions Architect
- Data Scientist
- Big Data Analyst
This certification improves your chances of getting well-paying jobs in data analysis, cloud infrastructure, and analytics leadership positions.
With hands-on practice in Amazon EMR, Apache Spark, and other AWS offerings, our course prepares you to lead teams that implement large-scale cloud data solutions. Learn to manage data pipelines and apply cost and performance optimization strategies in AWS environments. This will empower you to manage cloud-based infrastructure and qualify you for senior positions such as Cloud Solutions Architect or Lead Data Engineer.
The training covers interactive demos and hands-on lab exercises in which you'll use AWS tools like Amazon EMR, Apache Spark, and AWS Glue. These practical projects will help you to implement what you've learned in real-world applications, equipping you for actual challenges within data engineering jobs.
Our AWS certification proves proficiency in AWS data analytics solutions, batch data processing, and cloud infrastructure. It reflects your capabilities in managing large-scale data analytics projects, making you a strong fit for data engineering and cloud computing positions in any sector.
Sectors like technology, finance, healthcare, retail, and government actively hire professionals in AWS and batch data analytics. There are prospects in data engineering, cloud solutions, data science, and analytics leadership positions.
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