Data Warehousing System for Miller Inc

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.

In class we have learned about various business information systems that aid in organizations experiencing more time and cost efficient solutions to internal and external challenges. At Shoppers Drug Mart, multiple business information systems are utilised to maximize profit and productivity. A transaction processing system is used at the point of sale to maintain a record of every transaction, including refunds and voids. The system records if the transaction was paid for in cash, debit, credit, or a gift card and possesses other features as

TCS Company provided a solution to one of its client for changing hardware and software to existing database presented in client’s data warehouse for reutilization. Client is leading global provider for offering communication services, it delivers solutions to multinational Companies and Indian consumers (Tata consultancy). Company implemented a solution by replacing the existing hardware and software with TATA Company data warehouse

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

Data warehousing is defined as the design and implementation of processes and tools to manage and deliver complete, timely, accurate, and understandable data for decision making. It includes all the activities that make it possible for an organization to create, manage, and maintain a data warehouse or data mart (Williams & Williams, 2007). Data warehousing majorly deals with managing the development, the implementation, and the operation of a data warehouse or data store. It includes metadata management, data acquisition, data archiving, data cleansing, storage management, data integration, data distribution, security management operational

Furthermore, the Gartner website argues that “BI has become a strategic initiative and is now recognised by chief information officers (CIOs) and business leaders as instrumental in driving business effectiveness and innovation,” (Anon., 2007). Gartner also argues that “BI projects were the number one technology priority for 2007” (Anon., 2007). According to the Bill Inmon, data warehouse is “a subject-oriented, integrated, time variant and non-volatile collection of data used in strategic decision making”. Hammergen & Simon, (2009) define data warehouse more simpler by saying that “ Data warehousing is therefore the process of creating an architected information management solution to enable analytical and information processing despite platform, application, organizational, and other barriers.“ It is important to note that data warehouse system is different from relational database. The reasons of that are: (1) In the data warehouse data is stored for long term; (2) DW is designed for high performance for analytical queries; (3) its OLAP (Online Analytical Processing) technology enables to view data in various form; (4) linking between tables are simple (Tushman, 2014). Databases, in contrast, have a low performance regarding data analysis; joins between tables are

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

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.

This database provides general reports for. E.g. Daily Sales report by product or by customer or by route. These reports are helpful— particularly for real-time reporting —but they don’t allow in-depth analysis. The possibilities for reporting and analysis are endless. When it comes to analyzing data, a static list is insufficient. There’s an intrinsic need for aggregating, summarizing, and drilling down into the data. A data warehouse enables you to perform many types of analysis:

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

1) Key word "speed" - users have earlier access to data at any time (basically the smooth running of a company is assured of making correct decisions to be taken quickly based on data that is stored in a warehouse data, the speed of access becomes a necessity). If simple analysis response time is one second, and for more complex analysis, response time may be longer than 20 seconds;

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.

The text book Data Warehousing concepts, techniques, products and applications by C.S.R. Prabhu. Mainly, the text book gives the information about the data model, online analytical processing systems and tools, data warehouse architecture, data mining algorithms, organizational issues of the data warehouse, data warehouse segmentation, Application of data mining and data warehousing. Firstly, the book describes Data Warehouse is a system where it is used for reporting the data from the wide range of the sources and indeed it helps the company to guide the management decisions. Moreover, Data Warehousing is the process where it evolved with the transformation and extraction of data from the various applications. Identically, it also has a technique from the formulation of the business intelligence where it gives effective implementation which makes the Data warehouse the effective technology for the business use. Importantly, Data Warehouse is the division of data into the individual data component. Similarly, Data Warehouse helps to analyze the data and whereas they are technologies which helps to analyze the data available in the data warehouse. Indeed, the functions of the Data Warehouse tools are data extraction, data cleaning, data transformation. Mainly, the data extraction gathers the data from the multiple sources, data cleaning helps to find and correct errors in data, data transformation converts the data into data warehouse format. Consequently, data cleaning and