Questions On Online Analytical Processing

An active data warehousing, or ADW, is a data warehouse implementation that supports near-time or near-real-time decision making. It is featured by event-driven actions that are triggered by a continuous stream of queries that are generated by people or applications regarding an organization or company against a broad, deep granular set of enterprise data. Continental uses active data warehousing to keep track of their company’s daily progress and performance. Continental’s management team holds an operations meeting every morning to discuss how their

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.

There are several important steps to consider when designing a database, as a well-designed database should be deployed and not only support the accuracy and integrity of business information but also avoid redundant data and assist with has enterprise level reporting tasked. If we analyze the

Our tables can be widely classified into fact tables (measurements, e.g., impressions, clicks, conversions) and dimension tables (configuration, e.g., campaigns, lineitems, tactics). While processing data from fact tables, the requirement for related data from

Course Description This course covers database concepts. Topics include data analysis, the principal data models with emphasis on the relational model, entity-relationship diagrams, database design, normalization, and database administration. Policies Faculty and students will be held responsible for understanding and adhering to all policies contained within the following two documents: • • University policies: You must be logged into the student website to view this document. Instructor policies: This

Coronel, C. (2013). Database Systems: Design, Implementation, and Management, Tenth Edition. Mason, Ohio, United States: Cengage Learning.

Since 1960 and beyond the need for an efficient data management and retrieval of data has always been an issue due to the growing need in business and academia. To resolve these issues a number of databases models have been created. Relational databases allow data storage, retrieval and manipulation using a standard Structured Query Language (SQL). Until now, relational databases were an optimal enterprise storage choice. However, with an increase in growth of stored and analyzed data, relational databases have displayed a variety of limitations. The limitations of scalability, storage and efficiency of queries due to the large volumes of data [1] [2].

What are the perceived limitation of the star schema model? How did SAP’s extended star schema model address these issues?

All projects are working towards a Data Model that gets approved by engineering and business in the next few sprints. The goal is to provide self service reporting capabilities for the data relevant to respective business function.

A data model is a conceptual representation of the data structures that are required by a database [Mamčenko, J. (n.d.)]. The data structures gives the information about data objects, associations between data objects, and the rules which administer actions on the objects. A data model serves as a bridge between the concepts of the real world and how the data is physically organized in the actual database. Data modelling has been ongoing for many years but still businesses struggle to extract the value from their data and thus, create well designed, intuitive models [Data Modeling Best Practices. (n.d.).]. With businesses considering for innovative ways

The database used should be open and industry standard to allow easy integration with other applications and easy movement of data in the future. The database

Business intelligence systems combine operational data with analytical tools to present complex and competitive information to planners and decision makers. Their objective is to improve the timeliness and quality of the input to the decision process. Business Intelligence is used to understand the capabilities available in the firm; the state of the art, trends, and future directions in the markets, the technologies, and the regulatory environment in which the firm competes; and the actions of competitors and the implications of these actions. The emergence of the data warehouse as a repository, the advances in data cleansing, the increased capabilities of

The data warehousing system will also allow the company to use a data model and server technology that speeds up querying and reporting. This is because these will not be included in the data processing time thus allowing the company to use a modeling technique that does not slow down or complicate the transaction processing system. The data warehouse will also allow the company to use a bit-mapped indexing system as their server technology in order to speed up query and report processing. Technologies for transaction recovery will also be employed to speed up transaction

Current trend in the world of information technology is that relatively every organization is managing tens of petabyte of data. There are large proportion of data which need to be store and managed in database. So there is immense requirement of efficient and reliable database management system. Database systems need to be constructed in high reliability methods and techniques in terms of their functionalities and design. System Performance is an analytical metric that must need great output for an effective database system. Complex database system is outrageous and difficult to analyze so performance evaluation is very important concern since databases are one of the most compelling affair in today’s business revolution.

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,