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Building Data Analytics Solutions Using Amazon Redshift Training in Ethiopia

Learn to build & manage data analytics pipelines

8 hours of training program with eight modules

Integrate Amazon Redshift with a data lake

Guided instructive sessions from expert trainers

Includes interactive demos, practice labs & class exercises

Flexible learning & easy payment options available

GoogleGoogle4.9/5
5273 EnrolledEnrolled Learners
GoogleGoogle4.9/5
5273 EnrolledEnrolled Learners

Overview

What you will learn:

  • Supports practical use of data analytics in industries
  • Develops knowledge of the internal structure of Amazon Redshift
  • Prepares to navigate the Redshift console tools
  • Explains data loading & query techniques in Redshift
  • Teaches analysis of big data using Redshift Spectrum
  • Guides managing Redshift cluster security settings

Upcoming sessions

Curriculum

1

Data analytics use cases

2

Using the data pipeline for analytics

1

Why Amazon Redshift for data warehousing?

2

Overview of Amazon Redshift

1

Amazon Redshift architecture

2

Interactive Demo 1: Touring the Amazon Redshift console

3

Amazon Redshift features

4

Practice Lab 1: Load and query data in an Amazon Redshift cluster

1

Ingestion

2

Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with Data API

3

Data distribution and storage

4

Interactive Demo 3: Analyzing semi-structured data using the SUPER data type

5

Querying data in Amazon Redshift

6

Practice Lab 2: Data analytics using Amazon Redshift Spectrum

1

Data transformation

2

Advanced querying

3

Practice Lab 3: Data transformation and querying in Amazon Redshift

4

Resource management

5

Interactive Demo 4: Applying mixed workload management on Amazon Redshift

6

Automation and optimization

7

Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster

1

Securing the Amazon Redshift cluster

2

Monitoring and troubleshooting Amazon Redshift clusters

1

Data warehouse use case review

2

Activity: Designing a data warehouse 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.

Our Trainers

Learning Outcomes

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

  • 1

    Discover how Redshift supports modern data analytics and processing

  • 2

    Manage semi-structured formats using Redshift’s SUPER data type features

  • 3

    Run queries across large datasets using Redshift Spectrum integration

  • 4

    Tune & resize clusters to boost overall Redshift performance

  • 5

    Understand Redshift data distribution methods for efficient data handling

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    Prerequisites

    To enrol in this Building Data Analytics Solutions Using Amazon Redshift course in Ethiopia, candidates must fulfil these eligibility requirements:

    • A minimum of one year of experience managing data warehouses is required
    • Must have completed either AWS Technical Essentials or Architecting on AWS
    • Must have completed the Building Data Lakes on AWS course

    Overall ratings by our students

    Related courses

    Frequently asked questions

    The Building Data Analytics Solutions Using Amazon Redshift Training in Ethiopia is all about teaching professionals ways to design, build, and manage data analytics pipelines using Amazon Redshift. You learn to import, transform, and analyse large datasets, using tools like Redshift Spectrum and the SUPER data type.

    This Building Data Analytics Solutions Using Amazon Redshift course is beneficial to professionals from various fields, like -

    • Data Analysts
    • BI Analysts
    • Data Engineers
    • Cloud Data Engineers
    • Cloud Architects
    • Data Warehouse Developers
    • IT Professionals transitioning to data roles

    Professionals are issued a 100% refund upon withdrawing from the course within two days of registering by submitting a written request. The refund is processed within four weeks of approval.

    The course structure enables professionals to work with large, structured, and semi-structured datasets. The training also shows ways to connect Redshift with Amazon S3 for external data access.

    The Building Data Analytics Solutions Using Amazon Redshift Training explains both automation and performance tuning. The course covers topics like -

    • Resize clusters
    • Manage mixed workloads
    • Optimise queries and resources
    • Automate tasks in Redshift clusters

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