G. Satyanarayana Reddy et. al. / (IJCSE) International Journal on Computer Science and Engineering Vol. 02, No. 09, 2010, 2865-2873 DATA WAREHOUSING, DATA MINING, OLAP AND OLTP TECHNOLOGIES ARE ESSENTIAL ELEMENTS TO SUPPORT DECISION-MAKING PROCESS IN INDUSTRIES G.SATYANARAYANA REDDY 1 RALLABANDI SRINIVASU 2 M. POORNA CHANDER RAO 3 SRIKANTH REDDY RIKKULA 4 1. Professor & HOD-MBA in CMR College of Information Technology, Hyderabad, India 2. Professor & Director in St. Mary’s Group of Institutions, Hyderabad, India. 3. Associate Professor, MCA Dept. St.Mary’s College of Engg. & Technology, Hyderabad , India. 4. Associate Professor, MCA Dept. St.Mary’s College of Engg. & Technology, Hyderabad , India. Abstract: This paper provides an overview of Data warehousing, Data Mining, OLAP, OLTP technologies, exploring the features, applications and the architecture of Data Warehousing. The data warehouse supports on-line analytical processing (OLAP), the functional and performance requirements of which are quite different from those of the on-line transaction processing (OLTP) applications traditionally supported by the operational databases. Data warehouses provide on-line analytical processing (OLAP) tools for the interactive analysis of multidimensional data of varied granularities, which facilitates effective data mining. Data warehousing and on-line analytical processing (OLAP) are essential elements of decision support, which has increasingly become a focus of the database industry. OLTP is customer-oriented and is used for transaction and query processing by clerks, clients and information technology professionals. An OLAP system is market-oriented and is used for data analysis by knowledge workers, including managers, executives and analysts. Data warehousing and OLAP have emerged as leading technologies that facilitate data storage, organization and then, significant retrieval. Decision support places some rather different requirements on database technology compared to traditional on-line transaction processing applications. Keywords: Data Warehousing, OLAP, OLTP, Data Mining, Decision Making and Decision Support 1.Introduction: A data warehouse is a “subject-oriented, integrated, time varying, non-volatile collection of data that is used primarily in organizational decision making. ( Inmon, W.H.,1992) Typically, the data warehouse is maintained separately from the organization’s operational databases. There are many reasons for doing this. The data warehouse supports on-line analytical processing (OLAP), the functional and performance requirements of which are quite different from those of the on-line transaction processing (OLTP) applications traditionally supported by the operational databases. Data warehousing is a collection of decision support technologies, aimed at enabling the knowledge worker (executive, manager, analyst) to make better and faster decisions. It serves as a physical implementation of a decision support data model and stores the information on which an enterprise needs to make strategic decisions. The data can be stored in many different types of databases. One data base architecture that has recently emerged is the “data warehouse”, a repository of multiple heterogeneous data sources, organized under a unified schema at a single site in order to facilitate management decision-making. Data warehouse technology includes data cleansing, data integration and online Analytical processing. OLAP stands for analysis techniques with functionalities such as summarization, consolidation and aggregation, as well as the ability to view information from different angles. Ten years ago, Data Warehousing was largely unknown. Today, many companies are receiving considerable business value from their warehousing efforts. First American Corporation (FAC), a regional bank located in the Southeast, lost $60 million in 1990 and was operating under letters of agreement with regulators. A new senior management team developed a customer intimacy strategy with a data warehouse at the heart of the strategy. Using warehouse data, FAC was able to determine the profitability of all of their clients and products; develop programs to ISSN : 0975-3397 2865