Big Data Bootcamp

In a combination of presentations and practical hands-on exercises, our Big Data Bootcamp program can turn your IT professionals into big data specialists. Offering comprehensive training as well as consultancy services, our big data experts will cover the full spectrum of big data concepts, tools, technologies, and industry best practices. 

This intensive journey over two to three weeks is designed for participants looking to deepen their knowledge and understanding of big data, as well as to develop their practical skills with examples from real use cases that they can adapt to suit your specific business objectives. 

By choosing this program for your team, you can help your organization overcome challenges in analyzing data, provide the opportunity for creating high-quality products and services, and lead to better overall decision-making at the company level. 

Our curriculum is created by IT professionals with over 15 years of experience, and pioneers in the big data field, guaranteeing that the information imparted is not only theoretical but also hands-on. Our trainers have a proven track record of successful projects in analyzing data, having the expertise to equip your team with the necessary skills to extract valuable insights from your large sets of data. 

Concepts & Solutions: Analytics, Batch and Streaming Processing, Data Warehouse, Data Lake, Data Lakehouse, Data Mesh, and more.

This format can be customized and adapted according to your specific goals. On request, we can also add tools or technologies that you wish to work with in the future and develop a customized program to suit your strategic goals. 

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Main Topics

Theoretical Foundations of Big Data:

Understanding big data concepts and architecture

Data storage solutions: Warehouse, Data Lake, Data Lakehouse

Data Mesh philosophy and architecture

Data lifecycle stages: Ingestion, Storage, Transformation, Serving 

Data Quality and Management:

Ensuring data quality through metrics, validation, and monitoring

Big Data Processing with Spark:

Fundamentals of Apache Spark for large-scale data processing

Databricks and Delta Lake:

Utilizing Databricks for big data analytics

Managing and optimizing data with Delta Lake

Data Ingestion and Serving:

Techniques for data ingestion including CDC (Change Data Capture) and streaming

Querying and serving data from various sources including APIs

Data Transformation and Pipeline Orchestration:

Orchestrating data pipelines for batch and streaming processes

Leveraging Apache Spark and Kafka Stream for data transformation

Data Modeling and Storage Architecture:

Data modeling methodologies: 3NF, Inmon, Kimball, Data Vault

Storage architecture design: Medallion Architecture, layers, zones, tiers