Data Warehousing and OLAP Technology (Data warehousing)
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2017 by IJETT Journal|
|Year of Publication : 2017|
|Authors : Priyanka Jaroli, Palak Masson
|DOI : 10.14445/22315381/IJETT-V51P208|
Priyanka Jaroli, Palak Masson "Data Warehousing and OLAP Technology (Data warehousing)", International Journal of Engineering Trends and Technology (IJETT), V51(1),45-50 September 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Data warehousing and on-line analytical processing (OLAP)are essential elements, which has focus on the database industry. Many products and services are now available, and all the management concept is based on database management principle. Data warehousing is create using to approach (1)top down approach (2)bottom up approach . Decision support places database technology is used but in different- different ways. compared both traditional on-line transaction processing and modern on-line transaction processing applications. This paper provides an overview of data warehousing and OLAP technologies. We describe back end tools for extracting, cleaning and loading data into a data warehouse; multidimensional data models are typical to use in OLAP; Now describe front end client tools for querying and data analysis; server extensions for efficient query processing; and tools for metadata management and managing the warehouse. In this paper also identifies some research and database problem .this technology is presented at the VLDB Conference, 1996.
 Inmon, W.H., Building the Data Warehouse. John Wiley, 1992.
 Data Modeling Techniques for Data Warehousing Chuck Ballard, Dirk Herreman, Don Schau, Rhonda Bell, Eunsaeng Kim, Ann Valencic
 Zhuge, Y., H. Garcia-Molina, J. Hammer, J. Widom, “View Maintenance in a Warehousing Environment, Proc. Of SIGMOD Conf., 1995
 Data Warehousing Fundamentals: A Comprehensive Guide for IT Professionals. Paulraj Ponniah Copyright © 2001 John Wiley & Sons, Inc.
 Principle Partners, Inc. Info@PrinciplePartners
 Roussopoulos, N., et al., “The Maryland ADMS Project: Views R Us.” Data Eng. Bulletin.
 O’Neil P., Quass D. “Improved Query Performance with Variant Indices”.
 O’Neil P., Graefe G. “Multi-Table Joins through Bitmapped.
 Harinarayan V., Rajaraman A., Ullman J.D. “ Implementing Data Cubes Efficiently”.
 Chaudhuri S., Krishnamurthy R., Potamianos S., Shim K. “Optimizing Queries with Materialized Views”
 Yang H.Z., Larson P.A. “Query Transformations for Queries”
 Widom, J. “Research Problems in Data Warehousing.”
 http://en.wikipedia.org/wiki/ olap design metholodegy  Agrawal S. et.al. “On the Computation of MultidimensionalAggregates”
Chatziantoniou D., Ross K. “Querying Multiple Features in Relational Databases”]
 Chaudhuri S., Shim K. “An Overview of Cost-based Optimization of Queries with Aggregates”.
ROLAP, MOLAP, redundant structures, rollup, drill down, slice-dice, pivot, Snowflake.