The Enterprise Data Warehouse : General Overview

The purpose of data warehousing is to combine all of a company 's data and allows users to access the data directly, create reports, and obtain responses to

Up until this point, Third Star Financial Services has operated via a succession of mergers and acquisitions where systems were inherited but never integrated into the network. Its data management has been virtually non-existent and entirely ineffective. Evidence of this can be found in the absence of an enterprise-wide data management solution and the presence of several disparate systems operating independently with no measurable benefit to the company. Due to a lack of actionable data, management makes decisions based on instinct rather than through analysis. A direct consequence of this is a steadily declining market share and loss of high-level employees to competing companies. Fortunately, this discrepancy has been identified and Third Star executives have established the new goal of modernizing and streamlining operations. Using concepts outlined by the Data Management Association (DAMA), this proposed enterprise architecture will allow Third Star to transform their data from a liability to an asset.

An enterprise data warehouse (EDW) makes information accessible to the applications utilized as a part of offices all through the association including engineering, human resources (HR), and strategic planning. Norfolk Southern assembled a TOP dashboard

This figure illustrates the future of BI for CTC. Independent data sources have been incorporated into a single BI system, within a global data model. All data will be loaded into corporate EDW via ETL. The EDW will feed the financial data mart for enterprise performance management, so business users will be able to conduct planning and budgeting functions. On the right side of the EDW, BI specialists will assist in organizing data marts into four categories: Supply Chain, Vendor,

An enterprise data model presents an abstraction of a more complicated real-world event or object. Generally, a data is graphical simple representation, of an interconnected real organization’s data structures. The main function of the data model is to help in understanding the complexities of a particular organization. A data model within a database environment brings out the data structures, their transformations, constraints, relations, and characteristics, thus providing a blueprint of

Data warehouse has different concepts of data. Each concept is divided into a specific data mart. Data mart deals with specific concept of data, data mart is considered as a subset of data warehouse. In Indiana University traditional data warehouse is unable to create large data storage. Further it shows any errors and imposed rules on data. The early binding method is disadvantage. It process longer time to get enterprise data warehouse (EDW) to initiate and running. We need to design our total EDW, from every business rule through outset. The late binding architecture is most flexible to bind data to business rules in data modeling through processing. Health catalyst late binding is flexible and raw data is available in data warehouse. It process result by 90 days and stores IU data without any errors.

One crucial thing that organizations need to consider in today’s unstructured data world is to successfully integrate data warehouses. For this, the companies need to re-consider their enterprise data architecture and classify the governance strategy that can be talented through such efforts. There lies a need for data managers

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.

3. Enterprise application integration (EAI) connects the plans, methods, and tools aimed at integrating separate enterprise systems.

Databases are the center of many technology and non-technology focused businesses. They are used in retail, healthcare, education and government. Databases are essentially in entering, storing, managing and referencing data, and can be simple in nature, or extremely complex. In order for a database to be implemented correctly, planning is required. Planning takes place from the moment of idea inception, and continues throughout multiple stages of the planning process (typically during the analysis and design phases). An Entity-relationship diagram, or ERD, is a visual layout or plan for a database. An ERD is defined as “a graphical model that shows the logical model of the data for an organization (Dischiave, n.d.).” ERDs should follow the industry standard best practices in order to be most effective and useful overall. ERDs that do not follow certain best practices, which are outlined in this paper, could cause delays, inconsistencies, or lasting problems when designing and implementing a database. ERDs should follow set business rules, follow appropriate, effective and consistent naming conventions, should clearly outline unary, binary and ternary relationships, should include attributes, entities and relationships and should be clear and easy to follow (Hoffer, 2012). The article entitled

The data warehouse comes ready for use, but an organization has to get prepared to use it. The main factor is data warehouse usage. A data warehouse can be used for decision making for management staff.

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

A common feature of data warehouse on which most of the scholars agree upon is that a data warehouse acts as storage of historical data. This

The data in a data warehouse comes from operational systems of the organization as well as from other external sources. These are collectively referred to as source systems. The data extracted from source systems is stored in a area called data staging area, where the data is cleaned, transformed, combined, deduplicated to prepare the data for us in the data warehouse. The data staging area is generally a collection of machines where simple activities like sorting and sequential processing takes place. The data staging area does not provide any query or presentation services. As soon as a system provides query or presentation services, it is categorized as a presentation server. A presentation server is the target machine on which the data is loaded from the data staging area organized and stored for direct querying by end users, report writers and other applications. The three different kinds of systems that are required for a data warehouse are:

ICICI Bank is India’s largest private sector bank. Thebank has a network of 4,050 branches and 12,919ATMs and offers customers a robust Internet bankingsolution. The bank has a presence in 19 countries,including its home market in India(ICICI). ICICI Bankoffers a wide range of banking products and financialservices to corporate and retail customers through avariety of delivery channels and through its specializedsubsidiaries and affiliates in the areas of investmentbanking, life and non-life insurance, venturecapital, and asset management.