際際滷shows by User: RalphWinters / http://www.slideshare.net/images/logo.gif 際際滷shows by User: RalphWinters / Fri, 12 Jul 2013 17:27:48 GMT 際際滷Share feed for 際際滷shows by User: RalphWinters Practical Text Mining with SQL using Relational Databases /slideshow/ralph-winters-text-analytics-sql-relational-database/24189100 ralphwinters-textanalyticssqlrelationaldatabase-130712172748-phpapp01
Presentation at the 11th Annual Text and Social Analytics Summit - Cambridge, MA. Integrate unstructured data within a relational database: Learn the feasibility, prototyping, value added, and the goals of Text Analytics. Understand how much data you have and the architecture necessary to leverage existing technology that goes along with your existing relational structure (Oracle, SAS, SQL Server, DB/2, Postgre, MySQL and others). Learn how to utilize sentiment analysis to determine propensity to churn. A best in practice discussion of statistic techniques, clustering, and association.]]>
Presentation at the 11th Annual Text and Social Analytics Summit - Cambridge, MA. Integrate unstructured data within a relational database: Learn the feasibility, prototyping, value added, and the goals of Text Analytics. Understand how much data you have and the architecture necessary to leverage existing technology that goes along with your existing relational structure (Oracle, SAS, SQL Server, DB/2, Postgre, MySQL and others). Learn how to utilize sentiment analysis to determine propensity to churn. A best in practice discussion of statistic techniques, clustering, and association.]]> Fri, 12 Jul 2013 17:27:48 GMT /slideshow/ralph-winters-text-analytics-sql-relational-database/24189100 RalphWinters@slideshare.net(RalphWinters) Practical Text Mining with SQL using Relational Databases RalphWinters Presentation at the 11th Annual Text and Social Analytics Summit - Cambridge, MA. Integrate unstructured data within a relational database: Learn the feasibility, prototyping, value added, and the goals of Text Analytics. Understand how much data you have and the architecture necessary to leverage existing technology that goes along with your existing relational structure (Oracle, SAS, SQL Server, DB/2, Postgre, MySQL and others). Learn how to utilize sentiment analysis to determine propensity to churn. A best in practice discussion of statistic techniques, clustering, and association. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ralphwinters-textanalyticssqlrelationaldatabase-130712172748-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presentation at the 11th Annual Text and Social Analytics Summit - Cambridge, MA. Integrate unstructured data within a relational database: Learn the feasibility, prototyping, value added, and the goals of Text Analytics. Understand how much data you have and the architecture necessary to leverage existing technology that goes along with your existing relational structure (Oracle, SAS, SQL Server, DB/2, Postgre, MySQL and others). Learn how to utilize sentiment analysis to determine propensity to churn. A best in practice discussion of statistic techniques, clustering, and association.
Practical Text Mining with SQL using Relational Databases from Ralph Winters
]]> 15686 23 https://cdn.slidesharecdn.com/ss_thumbnails/ralphwinters-textanalyticssqlrelationaldatabase-130712172748-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-RalphWinters-48x48.jpg?cb=1535721972 Experienced hands-on technical Project Manager, Data Analyst, Data Miner, Data Scientist, and Applications Programmer/Developer. Strong background in BI, OLAP, data analytics, Data Science, Data and Text mining, SAS, forecasting, data visualization, relational databases, statistical procedures, logistic regression, predictive data modeling, and database marketing. I have worked with many different databases and operating systems. Specialties: Data Analytics , ETL, SAS, Data Mining, Big Data, Text Analytics, BI, Business Intelligence,OLAP,Statistics,Database,Complex SQL Querying Industries: Credit Card, Insurance,Pharmaceutical/Healthcare,Banking,Finance, Direct Mail,Direct Marketing,... http://www.nsf.gov/