Workshop Data Warehouse, Data Mart and BI Systems
Our workshop “Building Data Warehouses, Data Marts, and BI Systems” is specifically tailored to the needs of analysts and DWH developers who want to gain a deep understanding of data warehouse and business intelligence projects. Participants will acquire practical know-how to efficiently design, model, and successfully develop professional data warehouse systems.
- Faster and more efficient processes
- Well-founded, data-driven decisions
- Future-proof and scalable process design
Further training opportunities – Datalakehouse, Data Science and AI
Data analysis for decision-makers
For executives and managers in the areas of controlling, finance, marketing and management.
Data science and AI
This workshop is aimed at decision-makers from marketing, sales and IT. You do not need any previous knowledge.
Data warehouse systems
Analysts and DWH developers as newcomers to data warehouse, data mart, and BI projects.
In-depth data warehouse know-how for analysts and developers
In a world where data-based decisions are the key to success, it is becoming increasingly important to organize, analyse and provide data efficiently. The more familiar employees are with the BI tools used, the more effectively they can use them. A well-trained team thus becomes a real competitive advantage for companies.
This workshop is specially designed for analysts and DWH developers who are new to data warehouse and business intelligence projects. We will teach you the basics in an understandable and practical way so that you can enter the world of data warehouses with a clear understanding and initial practical experience.
Arrange a free consultation nowModeling, optimizing, and extending data models – Data Warehouse in practice
Prerequisite: Basic IT knowledge
In our workshop, you will receive a thorough introduction to the methodology and key concepts surrounding data warehousing, data marts, and business intelligence (BI) systems. On the first day, we will cover the theoretical foundations, while on the second day, you will build a simple data warehousing system yourself in a practical setting – ideally using sample or demo data from your own company.
- Introduction to the terms and DWH concepts
- Data warehouse architecture: layers, components and characteristics
- Conceptual and logical modeling as well as semantic models
- Normalized vs. denormalized data models
- Multidimensional data models: Snowflake, Star Schema and Data Vault
- Shared dimensions and their significance
- Historically correct data storage: Slowly Changing Dimensions and BI-temporal storage
- Data storage in relational databases (file system, blocksize, extends, tablespaces, highwatermark, new formats)
- Partitioning and access types: full table scans, indices, hash keys, merge
- Performance tuning using examples (Oracle, SQL Server, DB2): Bitmap joins, filters, star joins
- Aggregates: Multigrain and multifact data models
- In-memory technologies
- Column-oriented databases
- Document-oriented databases and NoSQL data storage
- Analytical queries and cubes Best practices for building and optimizing data warehouse systems
- Open discussion and exchange of best practices
- Implementation of the workshop content using concrete practical examples
- Development of a simple data warehouse system Optional: Use of sample or demo data from your company
€
2495
unique
- Duration: 2 days
- Prerequisite: Basic knowledge of SQL*
- Presence / Online
Note: Short-notice appointments are possible
Practice-oriented and tailored to you
Analysts and DWH developers as starters in data warehouse and business intelligence projects
We design the content individually according to your requirements and respond flexibly to your questions – also using your own sample data. We combine the topic modules to create a training course that is perfectly tailored to your needs.
Contact
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Would you like more information or are you interested in a personal consultation? Simply let us know in a short message how we can help you, and we will get back to you as soon as possible.
Let’s begin.