Hdfc Bank 's Largest Private Sector Bank Essay

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

1.     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,

Banks are the most significant players in the Indian financial market. They are the biggest purveyors of credit, and they also attract most of the savings from the population. Dominated by public sector, the banking industry has so far acted as an efficient partner in the growth and the development of the country. Driven by the socialist ideologies and the welfare state concept, public sector banks have long been the supporters of agriculture and other priority sectors. They act as crucial channels of the government in its efforts to ensure equitable economic development.

In Philip Russom’s webinar he provides an overview of what a Data Warehouse (DW) modernization is, why many users’ DWs need modernization. The top five most common reasons for DW modernization including: Advanced Analytics, Scale, Speed, Productivity and Cost Control, what is the result from modernization, and his recommendations

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.

This report is mainly discussing the benefits brought to the bank industry by data warehouse- business intelligence application- with its several features such as, enhancing business intelligence, support decision making and improve the bank’s profitability with controlling costs. Then, the report is going to analyse the success of the St. George bank to prove that data warehouse is much significant BI application to help banks perform better than their competitors.

There is currently a very strong need for a defined and standardized process to request work related to the data warehouse. Not only does the work requests need to be standardized the development methodology needs to be defined with an agile approach fitting best with the direction and culture of the company. By clearly defining steps to both of these things the efficiency of the team will be greatly improved. They should be able to complete more projects as well as improve the quality of the products they are producing. With less mistakes and errors and more work being completed the return on investment for the data warehouse technology will be greatly increased.

A data warehouse (DW) can be acknowledged as one of the most complex information system modules available and it is a system that periodically retrieves and consolidates data from the sources into a dimensional or normalized data store. It is an integrated, subject-oriented, nonvolatile and a time-variant collection of data in support of management’s decisions (Inmon, 1993).

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

Teradata offers both traditional and emerging logical data warehouse solutions. Teradata product delivery is in such a way that it always leads and faces least competition in overall execution. It has constantly pushed the market towards emerging best practices and product innovation. Teradata has different form factors ranging from tiny proof of concept (POC) solutions to an all-flash-memory, enterprise-capable solution. It is a leader in logical data warehouse with its unified data architecture which combines Teradata, Aster and Hadoop technology.

The success of the database and data warehouse (DW) project really depends on the quality of data. If data quality is not good enough, the information will logically be unreliable when the business users retrieve it from the database/DW environment. Good quality of data will be useful for the decision maker to make the right decision, gain more trust and make the organization more efficient. In contrast, the bad quality of data will drive the decision maker to make a wrong decision.

Every organizations have their own independent Data Warehouse and due to increase in the number of transactions, the size of the data is also increasing. Data warehouse is the central repository of information for an organization. There are multiple data sources like OLTP, excel, csv, txt, xml, etc, that are generated from various systems and are populated to data warehouse by ETL and thus Data Warehouse stores the summarized integrated business data in a central repository. The Data Warehouse is used for the analytical applications (OLAP – On-Line Analytical Processing), decision making, data mining and user applications.

Database servers are expected to reach the needs of the business, market and end users by providing tremendous performance. Since companies are moving towards “big data” technology to support larger audience there is always a need to have a performance enriched data warehouse server running behind to accommodate the needs of end users. A traditional database server is capable of handling gigs of data, providing a minimal amount of performance. This is due to the restricted amount of pre-defined configurations and parameters the servers come with. A traditional database server cannot match up the performance of a data warehouse server running on a massively parallel asymmetrical engine.

21  7.1)The Role of Reserve Bank of India (RBI) – Banker’s Bank: ......................................................... 23  7.1.1)Main Objective: ................................................................................................................. 23  8)Co‐operative Banks: ........................................................................................................................ 26  8.1)There are two main categories of the co‐operative banks. ....................................................... 27  8.1.1)Features of Cooperative Banks .......................................................................................... 27

Indian Financial Sector is a well diversified arena experiencing high growth and development. The financial sector of India is comprised of commercial banks, insurance companies, non-banking cooperations, pension and mutual fund houses and lot more other financial institutions serving the Indian Economy. However, the financial sector is a major ly dominated by the Bankin Sector where the commercial banks comprise of 60 percent of total assets held by the financial system followed by Insurance Sector. Apart from the Banks and Insurance Companies, financial sector also comprise of Non-Banking Finance Companies also known as NBFC which in operate in specialized segments of micro finance,