AI & Data

Big Data Technologies in the Cloud Training

The Big Data Technologies in the Cloud training is an intensive, practical workshop designed for engineers, system administrators, and IT professionals who want to learn how to effectively build and manage modern Big Data infrastructure in cloud environments (AWS, Azure, Google Cloud).

Duration
6h
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Who it's for

Ideal for teams that…

1 Software engineers and system administrators implementing or maintaining Big Data solutions in the cloud
2 Data analysts and Data Science professionals who want to increase their competencies in data processing and analysis
3 Individuals planning to migrate existing systems or deploy new projects based on Big Data and public or hybrid cloud environments
4 IT solution architects who want to implement modern, scalable data platforms
Outcomes after the program

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

✓

You will learn the architectures and capabilities of major Big Data and cloud technologies

✓

You will master effective techniques for storing, securing, and processing large datasets using tools like S3, Hadoop, Spark, and NoSQL

✓

You will gain skills in automating data integration and analysis using dedicated cloud services

✓

You will acquire practical experience in designing, deploying, and optimizing Big Data solutions in cloud environments

Program · 3 modules

What we actually do

M01
Day 1: Big Data Fundamentals in the Cloud
  • · Introduction to the Big Data concept and the 5Vs (volume, velocity, variety, veracity, value)
  • · Overview of cloud types: IaaS, PaaS, SaaS
  • · Main cloud service providers
  • · Compute: EC2, Lambda
  • · Storage: S3, EBS, Glacier
  • · Networking: VPC, Internet Gateways
  • · Monitoring: CloudWatch, CloudTrail
  • · Security and identity management: IAM
  • · Building a Data Lake in the cloud
  • · Amazon S3, Azure Blob Storage, Google Cloud Storage
  • · Managing permissions, data versioning, and data security
M02
Day 2: Data Processing and Analysis
  • · Distributed file systems in the cloud (HDFS, S3 integration)
  • · Hadoop
  • · Spark (AWS EMR, Azure Databricks)
  • · MapReduce
  • · YARN
  • · NoSQL technologies: HBase, Cassandra, MongoDB in the cloud
  • · Data warehouses: Amazon Redshift, Google BigQuery, Azure Synapse Analytics
M03
Day 3: Advanced Technologies and Case Studies
  • · Data integration services: AWS Glue, Azure Data Factory, Google Dataflow
  • · Workflow orchestration and automation: Oozie, AWS Step Functions
  • · Cloud data analysis: Athena, BigQuery, Spark SQL
  • · Data visualization: Jupyter Notebook, Zeppelin, BI tools
  • · Security: secret storage, access auditing, compliance (IAM, Azure Key Vault)
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.

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