The Storage Of Data Warehouse Essay

Real-time data warehousing creates some special issues that need to be solved by data warehouse management. These can create issues because of the extensive technicality that is involved for not only planning the system, but also managing problems as they arise. Two aspects of the BI system that need to be organized in order to elude any technical problems are: the architecture design and query workload balancing.

This data is collected and organized in order to process orders and maintain good customer service. The logical view of data would allow a knowledge worker to arrange and access information based on the needs of the business separating it from the physical view of how information is arranged and stored. The ability to do this allows for an employee to create detailed reports in order to determine information such as customer information and their order numbers and dates. This is imperative for a company like Comcast who has over 27 million customers in order to have a system to keep important data to analyze. Using a data warehouse allows them to gather from several databases and then the company can use the information to determine for example how many units of voice products are sold to create the necessary business intelligence to make future decisions and remain

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.

The writer finds two problems that are going too analyzed in this study. In addition, the problems are:

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

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

Extraction, Transformation, and Loading processes are responsible for the operations taking place in the back stage of a data warehouse architecture. In a broader aspect, initially the data is extracted from the source data stores which could be On-Line Transaction Processing or Legacy system, files of any formats, web pages or any other documents like spreadsheets or text documents. In this step, only the data which is different from the previous execution of ETL process (newly inserted, updated) gets extracted from the sources. Next, the extracted data is sent to Data Staging Area where the data is transformed and cleaned. Finally, the data is loaded to the central data warehouse and all its counterparts e.g., data marts and views. (Kabiri & Chiadmi 2013, p.1)

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.

Harrah’s had initially used enterprise data warehouse from Teradata. They have now expanded their database system since their customer base has increased. They make use of Teradata Priority Scheduler and Teradata Dynamic Query Manager. In order to protect their system from external attackers and to ensure total safety, Harrah’s makes use of Teradata Dual Active Solutions. This system is useful to identify customers that come for the first time and it provides services and offers tailor made for them. The system can also alert the staff of a customer who has returned after a very long time and make a customized greeting for such return customers. This will make the customers feel special

1.Offload data & ETL processing to Hadoop : - This step will leverage high CPU consuming ETL processes which were earlier executed on data warehouse causing performance degradation and slow reads and in addition will free space from data warehouse by offloading low-value or infrequently used information onto Hadoop.

Article, www.coppereye.com/data_warehousing, states the aspects of return on investment of data warehouse is "the architectures have typically placed a premium on storing large volumes of data, and being able to execute queries very rapidly against this data." Real-time, with current information, is what is available with all the new data warehouse technology. Also, the article states, "it is common practice that loading the data is done overnight, and in many cases taken much longer with the growing success of data warehouse projects." Another aspect is, "business owners are no longer willing to accept reporting on last week's or even yesterday's performance, but want immediate access to data and reports about what is happening in the business to make ever more time-critical decisions.":

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 solve a lot of problems to companies as it helps to structure files and avoid unnecessary duplication of data.