Name: Mubbara
Roll no: 139
Topic: Basic Concept of Data
Warehouse
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Basic Concepts of Data Warehousing and OLTP/OLAP Systems, Summaries of Data Mining
An in-depth exploration of the origins, key concepts, and differences between data warehousing and operational database systems (oltp). It delves into the development of the data warehouse concept, the role of bill inmon, and the advantages of data warehousing for heterogeneous database integration. The document also explains the query-driven and update-driven approaches, data cleaning, and data integration in data warehousing. Furthermore, it compares oltp and olap systems, highlighting their characteristics, orientations, users, functions, data types, access patterns, user numbers, database sizes, and processing speeds.
Typology: Summaries
2023/2024
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Name: Mubbara
Roll no: 139
Topic: Basic Concept of Data
Warehouse
Basic Concept of Data Warehouse:
- The concept of data warehouse first came into use in the 1980s when
IBM researchers Paul Murphy and Barry Devlin developed the
business data warehouse.
- American computer scientist Bill Inmon is considered the father of the
data warehouse due to his authorship of several work.
- In the absence of data warehousing architecture, a vast amount of
space was required to support multiple decision support
environments
- A data warehouse refers to a data repository that is maintained
separately from an organization’s operational databases.
- A data warehouse may contain multiple databases.
- Subject-oriented: A data warehouse target on the modeling and analysis of data for decision-makers. Therefore, data warehouses typically provide a concise and straightforward view around a particular subject, such as customer, product, or sales, instead of the global organization's ongoing operations.
- Integrated: A data warehouse is usually constructed by integrating multiple heterogeneous sources.
- Time-variant: Data are stored to provide information from an historic perspective.
- Nonvolatile: Non-volatile means the previous data is not erased when new data is added to it.
Operational Database Systems: The major task of online operational database systems is to perform online transaction and query processing. These systems are called online transaction processing (OLTP) systems. They cover most of the day-to-day operations of an organization such as purchasing, inventory, manufacturing, banking, payroll. Data Warehouses: Data warehouse systems, on the other hand, serve users or knowledge workers in the role of data analysis and decision making. Such systems can organize and present data in various formats in order to accommodate the diverse needs of different users. These systems are known as online analytical processing systems.
Comparison of OLTP and OLAP Systems
OLTP
- Access: read/write
- Number of records accessed: Tens
- Number of users: Thousands
- DB size: GB to high-order GB
- Processing Speed: Very Fast
OLAP
- Access: mostly read
- Number of records accessed: Millions
- Number of users: Hundreds
- DB size: ≥ TB
- Processing Speed: Comparitively slow