Building Data Analytics Solutions Using Amazon Redshift Training in US
Learn to build and manage data analytics pipelines
8 hours of training program
In-depth course structure with eight modules
Integrate Amazon Redshift with a data lake
Guided instructive sessions from expert trainers
Includes interactive demos, practice labs and class exercises
Flexible learning options designed for a busy schedule
Hassle-free payment options in instalments
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4.9/55658 EnrolledEnrolled Learners
Overview
- Explore real-world uses and applications of data analytics
- Understand how Amazon Redshift is structured for data warehousing
- Get practical experience using the Amazon Redshift console
- Learn how to load data and run queries in Redshift clusters
- Use Amazon Redshift Spectrum to analyse large datasets
- Work with Jupyter notebooks for importing and analysing data
- Learn how to secure and monitor Redshift clusters effectively
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.
Learning Outcomes
After you complete this training, you will be able to:
1
Understand how Amazon Redshift is built and how it fits into data analytics workflows
2
Learn how to work with semi-structured data using the SUPER data type in Amazon Redshift
3
Build skills in using Redshift Spectrum to run queries on large datasets stored in Amazon S3
4
Apply best practices to resize and tune Redshift clusters for better performance
5
Develop advanced knowledge of how data is stored and distributed in Amazon Redshift
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 this Building Data Analytics Solutions Using Amazon Redshift Training in Sweden, 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
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Frequently asked questions
Our Building Data Analytics Solutions Using Amazon Redshift Training in the US is an interactive, instructor-led course. Professionals learn how to use Amazon Redshift to design, develop, and optimize data analytics solutions. It is a cloud-based data warehouse service offered by AWS. Data engineers, data warehouse developers, cloud architects, and IT specialists will find this course excellent.
You can look for jobs such as:
- Big Data Engineer
- Cloud Data Engineer
- Business Intelligence Analyst
- Data Warehouse Consultant
- AWS Data Specialist
Most hiring companies look for talent that can create and tune Redshift clusters to perform effective analytics.
Yes, this training is commonly offered both in online real-time format and in self-study recorded versions. Numerous academies also offer downloadable materials, lab access, and personalized support to support remote learning.
The professionals must know about fundamental AWS services, SQL, and data warehousing principles. The candidates should have some experience with tools such as S3, IAM, and EC2 so that they can easily understand Redshift concepts and gain hands-on practice while training.
Applicants must have at least one year of data warehouse management experience. They should have completed some of the foundational courses in AWS, such as AWS Technical Essentials or Architecting on AWS, preferably Building Data Lakes on AWS. This provides a solid basis for Redshift-based analytics learning.
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