19/12/2019
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Fundamentals of data warehouses - course 44,500 rub. from IBS Training Center, training 24 hours, Date November 26, 2023.
Miscellaneous / / November 30, 2023
During the course, you will become familiar with the basic concepts and challenges that arise when creating data warehouses. Understand how goals influence the choice of architecture and what consequences can result from insufficient attention to components. Get an idea of the roles and influence of team members on the result. The course program will describe practical approaches to the design and implementation of data warehouses and its components. You will look at life cycle management, including decommissioning and migration to new systems, and cover topics of data management and building services based on it. In the practical part, students will be divided into two teams: one of the teams will work on a storage migration project data taking into account the strategic development goals of the enterprise, and the second will evaluate it in terms of capabilities, resources and deadlines.
Topics covered:
1. Introduction (theory + practice 2.5 hours).
The concept of “data warehouse”. Its capabilities and limitations
Why is DWH created, what business problem does it solve?
2. Components and architecture (theory + practice 3 hours).
Classic approaches to data warehouse design
Typical components and processes involved
Inmon, Kimball and DataVault concepts
Overview of the main components (stage, ods, dds, datamart, bi, metadata) and processes (ETL, ELT, DQ, lineage)
3. Data management - Data Governance (theory + practice 2 hours).
General and specific issues of enterprise data management
Information is viewed as an asset that brings value and has costs to obtain.
The concept of “master data” and systems for their management - MDM
4. Storage design techniques (theory + practice 5 hours).
Storage Design Steps
Typical techniques and tools for creating
Expertise of participants and infrastructure
5. Source data storage area - Stage (theory + practice 3 hours).
The need to store raw data from the source system
Typical mistakes when organizing this area and its difference from a “data lake”
6. Permanent storage areas - ODS and DDS (theory + practice 3 hours).
Operational and multidimensional data storage layers
Processes of extraction, purification, control and preservation - ETL\ELT
Transformation to target storage scheme
7. Storage data consuming systems (theory + practice 3.5 hours).
Typical scenarios for using data from storages
Main consumers - business intelligence systems "BI"
The structure of a typical BI system and the reasons for their wide variety
8. New challenges in the development of data warehouses (theory + practice 2 hours).
An overview of the main challenges storage facilities face as they grow
New challenges in machine learning
The Data Mesh concept as an alternative for further development.
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