Textbook Notes (363,220)
Canada (158,272)
York University (12,359)
ADMS 2511 (123)
Chapter 4

Chapter 4 Notes.doc

4 Pages
Unlock Document

York University
Administrative Studies
ADMS 2511
Cristobal Sanchez- Rodriguez

Data Warehousing - companies are using data warehousing, and data mining tools to make it easier and faster for users to access, analyze and query data - data mining tools allow users to search for valuable business information in a large database or data warehouse Describing the Data Warehouse - Data warehouse: is a repository of historical data organized by subject to support decision makers in the organization - data warehouses facilitate business intelligence activities such as data mining, decision support and querying applications Basic Characteristics of Data Warehouse: - Organized by business dimension or subject: data organized by subject and contain information relevant for decision support and data analysis - Consistent: all data must be coded in a consistent manner - Historical: data kept for many years, so it can be used for trends, forecasting and making comparisons over time - Nonvolatile: data is not updated after it is entered into the warehouse - Has the ability to use online analytical processing: databases use Online Transaction Processing (OLTP) where business transactions are processed online as soon as they occur, objective speed and efficiency. Online Analytical processing (OLAP) involves the interactive analysis of accumulated data by end users - Multidimensional: data warehouse stores data in more than two dimensions. A common representation for this multidimensional structure is the data cube. - Relationship with Relational Databases: the data in data warehouses comes from the company’s operational databases which can be relational databases. The organizations data is stored in operational systems. Using special software called extract, transform and load (ETL) the system processes the data and then stores it in a data warehouse. Within the warehouse the data is organized in a form that is easy for end users to access. Diagram on page 121. Benefits of Data Warehousing: - End users can access needed data quickly and easily via web browsers because they are located in one place - End users can conduct extensive analysis with data in ways that may not have been possible before - End users can have a consolidated view of organizational data - The benefits can improve business knowledge, provide competitive advantage, enhance customer service and satisfaction, facilitate decision making and streamline business processes. Drawbacks: - expensive to build and maintain - incorporating data from obsolete mainframe systems may be difficult & expensive - people in one department might be reluctant to share data with other department - since data is transferred from other systems, it may go through a cleansing process that changes the information meaning that the data is not the system of historical record an does not fully represent the actual accounting systems Data Marts - because data warehouses are so expensive, they are used primarily by large companies - many other firms employ a lower cost, scaled down version of a data warehouse called a data mart - A data mart: is a small data warehouse that is designed for the end user’s needs in a strategic business unit (SBU) or a department - data marts can be implemented more quickly often in less than 90 days - also since they contain less information than a data warehouse, they have a more rapid response and are easier to learn and navigate - they support local rather than central control by conferring power on the user group - discussed databases, data warehouses, and data marts as systems for managing organizational data - companies finding that over time their data has developed problems - therefore to address these problems, companies must develop an enterprise wide approach to managing their data, this approach is called Data Governance. Data Governance - over time organizations have developed information systems specific for business processes, such as transaction processing, supply chain management, customer relationship management and other processes - information systems that specifically support these processes impose unique requirements on data, which result in repetition and conflicts across an organization - for example, the marketing function might maintain information on customers, sales territories, and markets which duplicates data within the billing or customer service functions - this situation produces inconsistent data in the enterprise, and prevents a company from developing unified view of core business information – data concerning customers, products, finances and so on – across the organization its information systems - two other factors complicate data management, first government regulations have made it a top priority for companies to better account for how information is being managed with their organizations (Sarbanes Oxley Bill) - Regulations can place intense pressure on corporate executives - if their companies lack satisfactory data management policies and fraud or a security breach occurs, they could be held personally responsible and face prosecution. - second companies are drowning in data, much of which is unstructured. - Data Governance: approach to managing information across an
More Less

Related notes for ADMS 2511

Log In


Don't have an account?

Join OneClass

Access over 10 million pages of study
documents for 1.3 million courses.

Sign up

Join to view


By registering, I agree to the Terms and Privacy Policies
Already have an account?
Just a few more details

So we can recommend you notes for your school.

Reset Password

Please enter below the email address you registered with and we will send you a link to reset your password.

Add your courses

Get notes from the top students in your class.