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Blazejewski Project Deliverable 4 Analytics Interfaces And Cloud Technology

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Blazejewski Project Deliverable 4 Analytics Interfaces And Cloud Technology
Project Deliverable 4: Analytics, Interfaces, and Cloud Technology
By: Justin M. Blazejewski

CIS 499
Professor Dr. Janet Durgin
25 November 2012

Introduction
Business Analytics means the practice of iterative and methodological examination of a business’s data with a special emphasis on statistic making. Business Analytics can further help businesses automate and optimize their business processes. Companies in which data plays a pivotal role, treats its data as a corporate assets and leverages it for gaining competitive advantage. A successful business analytics would typically depend on data quality, highly skillful and experienced professionals who understand the technologies, knows how to work with it and also understands the organizations processes in depth. Apart from this, the organization should have a capable infrastructure to support the operations of business analytics.

Usage of Business Analysis is done for the following purposes:
Exploration of data so as to find patterns and trends
Identifying relationships in key data variables for forecasting. For instance next probable purchase by the customer
Drilling down to the results to find out why a particular incident took place. This approach is done by performing statistical analysis and quantitative analysis with business analytical tools
Predicting future results by employing predictive modeling and predictive analytics
Testing previous decisions using A/B and Multivariate testing
Assisting business in decision making such as figuring out the amount of discount to be given for a new customer

Post identifying of business goal, an analysis methodology needs to be selected and the data is acquired to support the analysis. This data acquisition normally involves extracting data from systems that may be spread throughout different locations and facilities. The extracted data is then cleansed and integrated into a single repository such as a data mart or a data warehouse. Since the data

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