2007 T DWI BEST PRACTICES REPORT PREDICTIVE ANALYTICS Extending the Value of Your Data Warehousing Investment By Wayne W. Eckerson Sponsored by FIRST QUARTER 2007 TDWI BEST PRACTICES REPORT PREDICTIVE ANALYTICS Extending the Value of Your Data Warehousing Investment By Wayne W. Eckerson Table of Contents Research Methodology and Demographics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 What Is Predictive Analytics? . . . . . . . . . . . . . . . . . . .
Premium Business intelligence Data management Data warehouse
The Five Types Of Analytics Michael Corcoran Sr Vice President &CMO 1 Session Agenda Why business analytics? Review the different types of analytics & common misconceptions Review the delivery methods for the operational users Propose holistic approach to expand enterprise analytics Value of integration and data quality to analytics Discussion 2 Analytic Quiz What do beer and business analytics have in common? In 1900 W.S. Gossett‚ an analyst at Guinness invented a distribution to analyze
Premium Business intelligence Learning Predictive analytics
Create a validation data set with 50% of the data. Use Decision Tree‚ Regression and Neural Network approached for building predictive models. Perform a comparative analysis of the three competing models on validation data set. Write down your final conclusions on which model performs the best‚ what is the best cut-off to use‚ and what is the ‘value-added’ from conducting predictive modeling? Upload the saved file with the assignment. I created 6 models for this project‚ which are DT1‚ DT2‚ Reg1‚ Reg2
Premium Regression analysis Prediction Statistics
all content not your own‚ whether the attributions are for direct quotes‚ a chart‚ a picture or paraphrased content. Epagogix: Predictive Analytics for the Movies Prepared for MSIT 3820 / MSPC 3920 Business Intelligence Pat Gillogly‚ Instructor Mary A. Student May 8‚ 2015 Introduction: The purpose of this paper is to explore the use of predictive analytics‚ and specifically artificial neural networks (ANN)‚ by UK-based industry analyst Epagogix‚ to determine the economic viability of films
Premium Scientific method Project management Management
employer insight into the personality and qualities that an applicant possesses. There are many types of surveys‚ assessments‚ and questionnaires that may measure areas such as skills‚ behaviors‚ motivations‚ and attitudes. One example is the Predictive Index‚ which indicates what type of person the applicant is and how they work with others. An Occupational Personality Questionnaire assesses 31 behavioral dimensions in managerial and professional staff. The Executive Achiever is a questionnaire
Premium Personality psychology Higher education Jeff Bezos
References: “Advantages and Disadvantages of Data Mining.” (n.d.). Retrieved from http://www.zentut.com/data-mining/advantages-and-disadvantages-of-data-mining/ Bose‚ Amitabh. Predictive analytics leads to better sales results‚ (n.d.). Retrieved from http://www.slideshare.net/WNSGlobalServices/predictive-analytics-helps-you-predict-customer-behavior “Think Before You Dig: Privacy Implications of Data Mining & Aggregation.” (September 2004). Retrieved from http://www.nascio.org/publications/documents/NASCIO-dataMining
Premium Mobile phone Predictive analytics Data analysis
Decision Making DCSN 300 Competing on Analytics by Thomas H. Davenport Analytics is the ability to collect and analyze data through a systematic approach with the objective to make the best decisions in a business. Due to its passed proven capacities and its huge potential to make a difference‚ Analytics has become much more than a tool: it is a “strategic weapon” in today’s Business context. Is Analytics a key element to success in Business today? Analytics is a multi-faceted and multi-disciplinary
Premium Business intelligence Decision making Data analysis
Introduction Analytics competitors are define as strategic technique used to evaluate outside competitors. The analysis seeks to identify weaknesses and strengths that a company’s competitors may have‚ and then use that information to improve efforts within the company. An effective analysis will first obtain important information from competitors and then based on this information predict how the competitor will react under certain circumstances (http://www.businessdictionary.com) All these
Premium Data analysis Decision making Business intelligence
Considering the level of competition in Business-to-Consumer (B2C) E-commerce environment and the investments required to attract new customers‚ firms are focusing on reducing their customer churn rate. Churn rate is the ratio of customers who part away with the firm in a specific time period. One of the best mechanism to retain current customers is to identify any potential churn and respond fast. Detecting early signs of a potential churn‚ recognizing what the customer is looking for by the switch
Premium Data mining Customer attrition Marketing
The New Frontier: Data Analytics Yvonne Mitchell Strayer University Professor Raied Salman Info Syst Decision-Making January 12‚ 2015 The New Frontier: Data Analytics What is data analytics? How has its use in business evolved over time? What are the advantages and disadvantages of using data analytics within a specific company or industry? Are there any challenges or obstacles that business management must overcome in order to implement data analytics? If so‚ is there a strategy that
Premium Business intelligence Data analysis Health care