![Business Intelligence Architecture
Existing BI architectures typically feature a unidirectional communication
flow between different components:
• The architectures only features a one-way data flow.
• The limitation of unidirectional data flow is that no adjustment or correction
is allowed on data source even if an error is found.
• If organizations want to correct the error, they have to repeat the entire BI
process especially that of the cleansing procedures again. To overcome
these problems, a two-way data integration flow [14] is suggested whereby
the cleansed data can be sent back to data sources to improve accuracy
and reduce cleansing work.](https://image.slidesharecdn.com/biassignment2-200320144724/85/ETL-and-its-impact-on-Business-Intelligence-10-320.jpg)
ETL and its impact on Business Intelligence
- 1. ETL and its impact on Business Intelligence Presentedby- Isha Pande(23)
- 2. Index Introduction to Business Intelligence Extract-Transform-Load Process Business Intelligence Architecture Five-layered BI Architecture Summary Bibilography
- 4. Business Intelligence The term Business Intelligence (BI) refers to technologies, applications and practices for the collection, integration, analysis, and presentation of business information. The purpose of Business Intelligence is to support better business decision making. RAW DATA BI MEANINGFULDATA
- 5. Business Intelligence Business Intelligence means better decision-making: Decision making is the important factor for the success of the organization. BI helps in the accurate and timely decision making by providing all the business information. Many large organization making faster, better and accurate decision making with the help of Business Intelligence.
- 7. ETL (Extract-Transform-Load) Process > Extract, Transform and Load (ETL) process is important component of BI. Summary EXTRACT TRANSFORM LOAD ANALYZE
- 8. ETL (Extract-Transform-Load) Process > Extract describes the gathering of data from various sources. > Transformation is modification to match a desired state. > Load is its import into a database or data warehouse. > Data Warehouse is predominantly used to store detailed summary data and metadata(data about data). > On the other hand, metadata include information on data themselves. They facilitate a process of extracting, transforming and loading data through presenting sources of data in the layout of data warehouses. Metadata are also used to automate summary data creation and queries management. > ETL processes take up to 80% of the effort in BI projects. A high performance is thereby vital to be able to process large amounts of data and to have a up-to-date database.
- 10. Business Intelligence Architecture Existing BI architectures typically feature a unidirectional communication flow between different components: • The architectures only features a one-way data flow. • The limitation of unidirectional data flow is that no adjustment or correction is allowed on data source even if an error is found. • If organizations want to correct the error, they have to repeat the entire BI process especially that of the cleansing procedures again. To overcome these problems, a two-way data integration flow [14] is suggested whereby the cleansed data can be sent back to data sources to improve accuracy and reduce cleansing work.
- 11. Business Intelligence Architecture Existing BI architectures lack support on metadata management: • A good BI architecture should include the layer of metadata. • A metadata repository is essential for business users to store and standardize metadata across different systems. • By having a well-structured metadata, organizations will be able to track and monitor data flows within their BI environment. • In addition, they will be able to ensure the consistency of definitions and descriptions of data that support BI components and thus avoid misunderstanding and misinterpretation of data
- 12. Business Intelligence Architecture Some of the architectures do not include operational data store (ODS) within the BI environment: • It is essential to implement ODS to provide current or near current integrated information that can be accessed or updated directly by users. • Through this way, decision makers will be able to react faster to changing business environment and requirements. • It is necessary to consider data staging area in the ETL (Extract Transform- Load) process. As most of the data from data source require cleansing and transformation, it is important to create a temporary storage for data to reside prior to loading into ODS or data warehouse.
- 15. Five-layered BI Architecture Data Source Layer: • The purpose of this layer is to identify the data source. It is very important for an or-ganization to know where all required data are from. • This layer can help not only to increase the reliability of data but also to improve data organizing. • There are two types of data sources used by BI applications: (a) Internal data source (b) External data source
- 16. Five-layered BI Architecture Data Source Layer: (a) Internal data source: The data which is obtained and maintained by the system inside the organization such as Customer Relationship Management system (CRM) and Enterprise Resource Planning system (ERP). Internal data source also includes all business operation related data such as sales data, customers data etc. (b) External data source: All data which are organized outside the organization are called external source for example, data from partners, data from suppliers, information from governmentsand so on.
- 17. Five-layered BI Architecture ETL Layer: • This layer focuses on three main processes: (a) Extraction (b) Transformation (c) Loading
- 18. Five-layered BI Architecture ETL Layer: (a) Extraction: Extraction is used to read data from different sources both internally or externally. (b) Transformation: Transformation is the process that converts the extracted data from its original form into the form which is needed. (c) Loading: Loading process is defined to put data into data warehouse. • The purpose of ETL layer is to guarantee that all extracted data are cleansed and are converted into right form and the data loads into target warehouse.
- 19. Five-layered BI Architecture Data Warehouse Layer: • This layer provides the storage for data which are in desired and reliable formats for further use whenever and wherever needed. • There are three components in data warehouse layer: (a) ODS (b) Data Warehouse (c) Data Marts
- 20. Five-layered BI Architecture Data Warehouse Layer: (a) ODS: Operational data store (ODS) is used to integrate data and load them into data ware-house. ODS operatesas a short-term memory since the data in ODS is updated frequently. (b) Data Warehouse: Data warehouse is a central storage of structured data. And all data in data warehouse are ready for analytical use. Unlike ODS, data warehouse is a long-term memory as the data are permanent. Both current and history data are stored in data warehouses. It is a subject- oriented, integrated, time-variant and non-volatile collection of data to support the managements’ decision making process. (c) Data Marts: Data mart can be considered as a sub-set of data warehouse. Usually, data mart consists of data from one single subject area and it is created directly from the data warehouse.
- 21. Five-layered BI Architecture End User Layer: • The end user layer consists of tools that display information in different formats to different users. These tools can be grouped hierarchically in a pyramid shape. As one moves from the bottom to the top of the pyramid, the degree of comprehensiveness at which data are being processed increases.
- 22. Five-layered BI Architecture Metadata Layer: • Metadata refers to data about data. • It describes where data are being used and stored, the source of data, what changes have been made to the data, and how one piece of data relates to other information. • In this architecture, Metadata management is applied to all other four layers. • The purpose of this layer is that by using the well- structured metadata, organizations is able to track and monitor the data flow in a BI solution. • Furthermore, it can help to avoid misun- derstanding of data.
- 23. Summary • BI supports decision making. • Extract, Transform and Load (ETL) process is important component of BI. • The Five-layered BI architecture draws a big picture showing how BI solution works. • Data are gathered from both internal and external sources. Then these sources will be extracted, transformed and loaded into data warehouse for further analytical use. • End users use different tools to analyze the data to meet the business requirements or needs. • All the data are managed by the metadata layer in the architecture.
- 24. Bibilography 1) Nitin Anand. ETL and its impact on Business Intelligence. New Delhi, February 2014 2) In Lih Ong, Pei Hwa Siew and Siew Fan Wong. A Five-Layered Business Intelligence Architecture. Selangor, Malaysia, 2011 3) Mengwei Lu. DiscoveringMicrosoft Self-serviceBI solution: Power BI. Helsinki, Finland, May 2014
- 25. Thank You!