Data Warehouse : A Company 's Information Accessible And Consistent

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

The data warehouse contains all the information that both the chain managers as well personnel can access. This information helps them see which products are selling, how much, where more important points of sales are, which are needed in inventory and which items needs to be checked for quality etc. Similarly these databases also contain solid information about consumers such as what is the ratio of repeat customers, what age group needs to be targeted for advertising, which new group is emerging and how to stay in touch with consumers about new products and sales.

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

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.

If I were to design Ben & Jerry's data warehouse I would use several dimensions of information. The first dimension would consist of the company's products; ice cream, frozen yogurt or merchandise. The marketing department has to know which products are selling, if Ben & Jerry's didn't know that their T-shirts are selling out as soon as they hit the stores, then they wouldn't be able to take advantage of the opportunity to sell the shirts. The second dimension would consist of the different areas of sales; US, Canada, Mexico, or Europe. I am not sure if they sell their ice cream in Mexico, but with data collection they can find out if their ice cream would be a better seller in the hot climate, rather than pushing for greater

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

In computing, a data warehouse (DW, DWH), or an enterprise data warehouse (EDW), is a database used for reporting and data analysis. Integrating data from one or more disparate sources creates a central repository of data, a data warehouse (DW). Data warehouses store current and historical data and are used for creating trending reports for senior management reporting such as annual and quarterly comparisons.

In today 's organizations, basic descision making procedures and day by day operations frequently rely upon information that is put away in an assortment of information stockpiling frameworks, arrangements, and areas. To transform this information into helpful business data, the information commonly should be consolidated, purified, institutionalized, and compressed. For example, data may be changed over to an alternate information sort or different database servers may store the vital information utilizing diverse patterns. Dissimilarities like these must be settled before the information can be effectively stacked to an objective target. After the plan and improvement of data warehouse as per the business prerequisites, the way toward combining the information into the information stockroom from different sources is to be thought of. Extract Transform Load (ETL) procedures are basic in the achievement of the Data Warehousing ventures. The way toward extricating information from one source (extract), changing it as per the outline of the data warehouse(transform) and stacking it into data warehouse (load) constitute ETL. As it were, ETL is the way toward extracting information from different information sources, changes it according to the prerequisites of the target data warehouse and effectively stacking it into the data warehouse (database). In the transformation procedure data is institutionalized to make it perfect with the target database along with data purifying

The picture below shows the relationships among the different components of the data warehouse architecture:

During ETL process, data from many sources will be extracted and integrated into data warehouse periodically. Extraction is a process to identified and retrieve all relevant data from the sources. The role of transformation is to cleansing the data and integrated different schema to defined schema in data warehouse. Meanwhile, loading is a process to physically move the data from operational system to data warehouse.

Before discussing the current data warehouse architecture in place at ICICI Bank, issues associated with it, especially due to immense data growth and different modalities of data sources, it would be appropriate to have a quick look at the data warehouse history and architectural framework and how ICICI Bank’s data warehouse has evolved over the years. Back in 2008 ICICI Bank used Teradata and was dependent on Teradata for its data warehouse. Back in those days the size of the data warehouse was 3TB. Because of the dramatic growth in the amount of data, user population and the source stations coupled with cost of scaling and maintenance as well as system availability,posed a problem for the bank in using their legacy data warehouse solution. The bank felt that its legacy data warehouse solution posed scalability issues and one of the major issues that bank faced was with their current

Before discussing the current data warehouse architecture in place at ICICI Bank, the issues and drawbacks associated with it due to immense growth and different modalities of data sources, it would be appropriate to have a quick look at the data warehouse history and architectural framework and how ICICI Bank’s data warehouse has evolved over the years. Back in 2008 ICICI Bank used Teradata and was dependent on Teradata for its data warehouse. Back in those days the size of the data warehouse was 3TB. Because of the dramatic growth in the amount of data, user population and the source stations coupled by cost of scaling and maintenance as well as system availability, posed a problem for the bank in using their legacy data warehouse solution. The bank felt that its legacy data warehouse solution posed scalability issues and the major issue that bank faced was with

Data is the raw materials of any information system. With the revolution of Information Technology we are improving our decision making process more quick and smart. Data warehouse technology is the process of collection, sorting, structural formation, analysis, storing and presentation of data. So we say that data warehouse is the technology is overall data management system in the organization.