Data Warehouse Tutorial
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. Data Warehouse Tutorial covers Data Warehouse Overview, Data warehousing Terminologies, DWH Architecture, What is ETL?, Business Intelligence Lifecycle?, DWH Technology, OLAP and Multidimensional Model, DWH External/Unstructured Data in Warehouse, Merits and Demerits of Using DWH, DWH Quality Management and tools used and advantages, Star Schema, 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)
|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 Upto 1 TB||100 MB to 1 GB|
|Number of records accessed||Millions||Fewer|
|Dimensional view of data||Multidimensional view||Flat relational view|
As we know that data warehouse works on OLAP (Online Analytical Processing) which is exactly different from OLTP (Online Transaction Processing). Following comparison will give show why OLAP is a way better concept than the conventional OLTP:
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