Data Warehouse And Data Warehousing

A data warehouse is a large databased organized for reporting. It preserves history, integrates data from multiple sources, and is typically not updated in real time. The key components of data warehousing is the ability to access data of the operational systems, data staging area, data presentation area, and data access tools (HIMSS, 2009). The goal of the data warehouse platform is to improve the decision-making for clinical, financial, and operational purposes.

Today businesses are investing many resources in building data warehouses and data marts to obtain timely and actionable information that will give them better business insight. This will enable them to achieve, among other things, sustainable competitive advantage, increased revenues and a better bottom line.

Data warehousing is a powerful business intelligence tool for maximizing the organization’s investment in the information technology. It is can be describe as a collection of decision support technologies, maid to allow executive, manager, and analyst, to make faster decisions.

"A data warehouse is a subject oriented, integrated, time variant, non-volatile collection of data in support of management 's decision making process". Source

Data warehousing is defined as the design and operation of processes and tools to manage and deliver complete, timely, accurate, and understandable data for decision making. It includes all the activities that make it possible for an organization to create, manage, and maintain a data warehouse or data mart. Data warehousing majorly deals with managing the development, the implementation, and the operation of a data warehouse or data store. It includes data management, data acquisition, data archiving, data cleansing, storage management, data integration, data distribution, security management operational reporting, analytical reporting, backup and recovery planning,

Data warehouses are targeted for decision supporting. Old, summarized and consolidated data is very much important than detailed as well as individual records. As data warehouses store consolidated data, possibly from several operational databases, for perhaps a very long time, they tend to be in orders of magnitude much greater than operational databases; enterprise data warehouses are projected to be hundreds of gigabytes to terabytes in size.

Data Warehousing also known in many industries as an Enterprise Data Warehouse is a system that contains a central repository of integrated data, often collected from multiple sources and is used to perform data analysis enabling the creation of detailed reports that contribute significantly to a corporation’s business intelligence. Data Warehousing emerged as a result of advances in the field of information systems over the last several decades. There are two major factors that drive the need for data warehousing in most organizations. First and foremost, businesses require an integrated, company-wide view of high-quality information to maintain and improve upon their strategic position. Secondly, information systems departments must separate information from operational systems to improve performance dramatically in managing company data. Critical to the success of a Data Warehousing system, Data mining allows for companies to create customer profiles, manipulate information easily, and provide knowledgeable access to the current state of their company. However, a reality that many companies often find out the hard way is that data mining and data warehousing does not work for them. As with many new tools or technology, companies may jump on the bandwagon without fully contemplating its potential weaknesses. In order to remain competitive in today’s business world, companies should consider implementing data warehouses, but only with

A Data Warehouse is simply a consolidation of data from a variety of sources that is designed to support strategic and tactical decision making. In other words, a data warehouse consist of different data sources provides access to the data that will expand frequency and depth of data analysis. Due to these reasons, data warehouse is the foundation for business intelligence. Its main purpose is to provide a coherent picture of the business at a point in time. Using various Data Warehousing toolsets, users are able to run online queries and 'mine" their data. Companies that build data warehouses and use business intelligence for decision-making ultimately save money and increase profit. Moreover, many successful companies have invested large sums of money in business intelligence and data warehousing tools and technologies. They believe that up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their very survival.

Many corporations are experiencing significant business benefits of using data warehouse technology. Users report gains in market competitiveness through increased revenue and reduced costs through information management. Data warehousing is thus a major issue within most organizations, and thus the development of a data warehouse with a strong base is essential. This paper aims to present the important concepts of Data Warehousing such as Data Warehousing tools and the benefits of Data Warehousing, that a manager must understand in order to execute a successful Data Warehousing project in his/her company.

Data warehouse are multiple databases that work together. In other words, data warehouse integrates data from other databases. This will provide a better understanding to the data. Its primary goal is not to just store data, but to enhance the business, in this case, higher education institute, a means to make decisions that can influence their success. This is accomplished, by the data warehouse providing architecture and tools which organizes and understands the

Data warehouse is a central repository integrating data from various operating systems for validation of data, prediction etc .Data Warehouse is a relational database used for analysis and query rather than transactional database. It is used to collect historical data from various sources, integrate, analyze a particular subject, report. Data warehouse is time variant i.e one can retrieve any older data and once data enters data warehouse it cannot change [1]. According to Ralph Kimball Data warehouse is “copy of transaction data constructed for analysis and query”[5]. Data is taken from various sources like marketing, sales, ERP etc.

Data warehousing is an efficient system which store the past as well as current data used for creating reports. Data warehousing system is used for decision making by analyzing the reports. A data warehouse is a relational database, which is designed for analysis and query. It helps an organization to consolidate and analyze data from different sources and make decision. A data warehouse environment consists of OLAP (On-Line Analytical Processing) engine, ETL (Extraction, Transformation and Loading) process, client analysis tools and other applications that manage gathering and delivering the data.

Data warehouse is aggregation of subject-oriented, integrated databases, which is designed to confirm DSS support. Now days these repository has become a focal point for DSS in organisation. These data repository used for online analytical Processing (OLAP), data mining and support queries. Decisions which are pending from a long time get resolved by analysing data warehouses. Another benefit of data warehouse is it improves the productivity by redesigning business process and work. It is challenging and technical undertaking because data comes from different sources and systems. There are some other organisational issues like sponsorship maintenance, scope avoidance and political issues. Because of these reasons data warehouse project get

The purpose of a data warehouse is to make the company’s information accessible and consistent. They need to have the information immediately available and in the same format. Warehousing is of no benefit to a company if they have to wait any length of time to receive the data. A warehouse has to be an adaptive and durable source of information for the business. The warehouse has to be flexible to meet the needed changes of a business, as the business grows; it is possible that additional information will need to be collected. The warehouse needs to have the ability to expand to meet the needs of the business. Warehousing would not be beneficial to a business if they have to seek a new warehouse source each time a change was needed; it would be costly for a business. A data warehouse must be a secure stronghold that protects the information, which is regarded as an asset to the business. In today’s society it this the utmost concerned of a business to make sure that their systems are not easily hacked by outsiders and their customer’s data is secured. Lastly, a warehouse is considered the foundation for decision making. It is the data that is retrieved from the system that is compiled for presentation to the decision makers of the company.

In the present juncture, data is the most significant entity for almost every type of organization. Be it software, hardware, healthcare, banking, government, scientific, etc., one of the most crucial part for the success of such organizations relies on how they manage their data and with the passage of time, amount of data is being increased radically which is making it quite difficult for the organizations to manage their data in an efficient manner.