Data Warehouse Tutorial for Beginners
This is a free tutorial that serves as an introduction to help beginners learn the various aspects of data warehousing, data modeling, data extraction, transformation, loading, data integration, and advanced features. This includes free use cases and practical applications to help you learn better.
This Data Warehouse Tutorial also covers a data warehouse overview, data warehousing terminologies, DWH architecture, ‘What is ETL?’, Business Intelligence life cycle, DWH technology, OLAP and multidimensional models, DWH external/unstructured data in the warehouse, merits and demerits of using DWH, DWH quality management and tools used and their advantages, star schema, and snowflake schema.
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Following are the benefits of deploying a strong data warehousing technology:
- Stored data is processed using statistical analysis, reporting, etc.
- Production strategies can be fine-tuned using the data warehouse information
- Customer buying preferences can be possible by analyzing DWH information.
Data Warehouse (OLAP) vs. Online Transaction Processing (OLTP)
As we know that data warehouse works on OLAP (Online Analytical Processing) which is exactly different from OLTP (Online Transaction Processing). The following comparison will give show why OLAP is a way better concept than the conventional OLTP:
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| Basis of difference |
DWH (OLAP) |
OLTP |
| Data types |
Transactional data |
Data from multiple sources |
| Suitable for |
Basic business operations |
Predicting future trends and analysis |
| Storage size |
From 100 GB up to 1 TB |
100 MB to 1 GB |
| Number of records accessed |
Millions |
Fewer |
| Dimensional view of data |
Multidimensional view |
Flat relational view |