Case Study: Active Data Warehousing

In the case of real-time analysis dashboards have become very popular over the past five years they provide a view of key metrics to allow management by exception. Where post transaction data is being analyzed, data warehousing provides the ideal methodology for enhanced forecasting from the data. This also allows the ability to look for improvements in the supply chain, operations, and marketing to adjust processes and refine a message for marketing as part of a continuous improvement program.

One of the main functions of any business is to be able to use data to leverage a strategic competitive advantage. The use of relational databases is a necessity for contemporary organizations; however, data warehousing has become a strategic priority due to the enormous amounts of data that must be analyzed along with the varying sources from which data comes. Company gathers data by using Web analytics and operational systems, we must design a solution overview that incorporates data warehousing. The executive team needs to be clear about what data warehousing can provide the company.

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

All warehouse and logistic company strives to improve its operational efficiency to ensure all transaction runs smoothly. Technology and materials handling revolution have become significant catalysts in the evolution of smarter and efficient warehouses. Yamato Transport needs to leverage technology that can give them access to actionable information that can be used in real-time. Identify whether workers needs to have access to mobile technology such as smartphones or other technology. In addition, software solutions also can give warehouse administrators a outlook of customers, orders and inventory, as well as computerize warehouse processes effectively. (Dragan,

What information is accessible? The data warehouse offers possibilities to define what’s offered through metadata, published information, and parameterized analytic applications. Is the data of high value? Data warehouse patrons assume reliability and value. The presentation area’s data must be correctly organized and harmless to consume. In terms of design, the presentation area would be planned for the luxury of its consumers. It must be planned based on the preferences articulated by the data warehouse diners, not the staging supervisors. Service is also serious in the data warehouse. Data must be transported, as ordered, promptly in a technique that is pleasing to the business handler or reporting/delivery application designer. Lastly, cost is a feature for the data

4. What elements of the data-warehousing environment at Continental are necessary to support the extensive end-user BI application

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.

The Fresh Direct has 300,000-square-foot headquarter and 1,500 employees. 8,500 products and 200,000 customers active in every day transaction. So every second there will be numerous data flowing into the company’s center. But the company lacks of a significant information system to deal with those data. They tried to use technology to convert the data to reports of real time information in order to

The Enterprise Data Warehouse is the primary data storage for USPS. It approximately 35 petabytes of storage capacity which allows it to store all the data collected from over 100 systems ranging from financial, human resources, transactional, etc. To process and store data into the EDW, it requires three steps of extract, transform and load. During the extraction process, the data is taken from the source of different systems within the USPS facilities. Then the transform process structures the data using rules or tables and turns it into one consolidated warehouse format. It also combines some data with others so it is easier to be transferred between different databases. The final process is the load with is basically integrating and writing the data into the database which can be accessed from any facilities and systems within the USPS. The EDW allows USPS to store any amount of data as efficient as possible at the lowest cost and quickest processing speed. It also allows the data to be used and migrate from database to database easily for analysis.

A data warehousing is defined as a collection of data designed to support management decision making. Data warehouses contains a wide variety of data that present a coherent picture of the business conditions at a single point in time. Development of a data warehouse includes development of the systems that extract data from operating systems plus the installation of the warehouse database system that provides managers flexible access to the data. The term data warehousing generally refer to the combination of many different databases across an entire enterprise. (webopidia)

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.

Design, code and deliver user friendly multi-tier business intelligence solutions that utilize data warehouse/data mining technologies to consume data across various database platforms and data stores.

The data warehousing system will also allow the company to use a data model and server technology that speeds up querying and reporting. This is because these will not be included in the data processing time thus allowing the company to use a modeling technique that does not slow down or complicate the transaction processing system. The data warehouse will also allow the company to use a bit-mapped indexing system as their server technology in order to speed up query and report processing. Technologies for transaction recovery will also be employed to speed up transaction

The main goal of this real-time data operation intelligence is to eliminate the data warehousing latencies. By achieving this, the organization can make better decisions hence able to make more rapid decisions.

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.