AI & Data

Amazon Redshift – Introduction Training

The "Redshift – Modern Data Analytics in the 21st Century" training is designed for individuals who wish to learn Amazon Redshift, a managed data warehouse used by leading companies.

Duration
6h
Who it's for

Ideal for teams that…

1 Individuals aiming to enhance analytical capabilities within their organization and derive insights from vast amounts of data collected daily.
2 Those interested in mastering the world's most popular data warehouse.
3 Anyone eager to understand how Redshift operates and how to design modern Data Lake solutions securely and efficiently.
Outcomes after the program

Hands-on AI and data analytics workshops — built around your team's real cases.

How Redshift operates and its architecture.

The evolution of Redshift and its functionalities.

The concept of decoupling storage and compute resources, exemplified by RA3.

Scalability features of Redshift, including automatic adjustment of compute resources.

Performance optimization techniques and data distribution strategies.

Best practices for data security and access management.

Creating and managing backups.

Loading data into Redshift clusters and integrating with S3.

Consuming data using Query Editor and JDBC/ODBC protocols.

Monitoring and auditing Redshift environments.

Building AI models using Redshift ML without prior ML tool knowledge.

Cost optimization strategies for Redshift usage.

Program · 11 modules

What we actually do

M01
How Redshift Works
  • · Understanding Redshift cluster architecture
M02
Redshift Evolution
  • · Navigating the array of Redshift functionalities
M03
Decoupling in Action
  • · Why separating storage and compute has become the standard
  • · RA3 nodes as an example of modern data warehouse architecture
M04
Redshift Scalability
  • · Automatic adjustment of compute resources to workload needs
M05
Redshift Optimization
  • · Performance-related factors
  • · Data distribution and its impact on query execution
M06
Redshift in Production
  • · Ensuring data security and access management
  • · Creating and managing backups
M07
Loading Data into Redshift
  • · Best practices for data loading
  • · Integration with Amazon S3
M08
Data Consumption from Redshift
  • · Using the visual Query Editor
  • · Accessing data via JDBC and ODBC protocols
M09
Monitoring and Auditing Redshift
  • · Observability and auditing of the data warehouse
M10
Redshift ML
  • · Building machine learning models directly from Redshift data
  • · Using ML capabilities without deep ML tool knowledge
M11
Cost Optimization
  • · Controlling and optimizing Redshift-related costs
Every module is adapted to your stack and context. The above is a starting point — not a fixed agenda.
How we work

From brief to retro in 30 days.

01

Brief & diagnosis

A call with the team lead + a short survey for participants. We define goals, gap and context.

02

Program customization

We adapt modules, case studies and code examples to your stack. Approval in 5 days.

03

Workshop

Trainer-led sessions, hands-on, code review. Mentor available between sessions too.

04

Retro + report

Outcome report for the team and lead. 30 days of consulting included.

Inquiry

Send a brief. We'll reply within 1 day.

After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.

Quote within 48h of the brief
First session within 30 days
Pilot before the full decision
VAT invoice, payment in instalments possible

Ochrona antyspamowa (Cloudflare Turnstile) zostanie aktywowana po wpięciu klucza.