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Archive for the ‘data mining intelligence’ Category

Basic Business Intelligence Reporting

January 23rd, 2012 1 comment

Take a CSV file and perform basic BI and reporting using a free tool.

Duration : 0:7:6

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GBI Mining Intelligence – Dragline and Truck / Loader training

January 15th, 2012 No comments

Through the thousands of years of data, GBI knows what it takes to be best practice, combined with our field trainers experience and opportunities recognised through interactions, we know what Dragline, Loader and Truck operators should be trained on!

How can you train effectively if you don’t know what best practice is?? We Do!

www.gbimining.com
gbi@gbimining.com

Duration : 0:3:1

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Chris Hote of Digimind – The Intelligence Collaborative Washington, DC 10/22/09

January 6th, 2012 No comments

Chris Hote of Digimind explains his company’s web tracking and visualization software.

Duration : 0:1:38

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BI Tutorial 12a Introducing Data Mining

December 29th, 2011 No comments

qsftdbmgthttp://gdata.youtube.com/feeds/api/users/qsftdbmgtTechBI, Tutorial, 12a, Introducing, Data, MiningBI Tutorial 12a Introducing Data Mining

Duration : 0:14:55

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Artificial Intelligence Lecture No. 17

December 21st, 2011 No comments

Video of the Lecture No. 17 in Artificial Intelligence at Ravensburg-Weingarten University from December 5th 2011. The Topics are:

Clustering:
– k-Means and the EM Algorithm
– Hierarchical Clustering
– Distance between Clusters
– Farthest Neighbour Algorithm

Data Mining in Practice
– The Data Mining Tool KNIME

Duration : 1:32:28

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SAS Customer Intelligence Drives Profitable Growth Opportunities

December 13th, 2011 No comments

With SAS Customer Intelligence, you can sharpen your focus on those customers, segments, and market offers that generate the most lucrative growth.

Learn more about SAS Customer Intelligence at: http://www.sas.com/software/customer-intelligence/profitable-growth-opportunities.html .

Duration : 0:2:38

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Data Mining Thesis, "business intelligence" , lingpipe , computer science

December 5th, 2011 No comments

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Writing a Good Data Mining Thesis
Data Mining Thesis Should Address Various Aspects of the Data Mining Process
Writing a Data Mining Thesis is a challenge. To write a proper thesis on the subject, one should understand what data mining is. It is not restricted to collection, extraction or processing of data. It is actually the identifying of various patterns in data. Though this is a relatively new subject, identifying patterns within a collection of data has been used by humans for centuries. Earliest scientific approaches to the subject are Baye’s Theorem and Regression Analysis in 18th and 19th centuries. During the past two decades, data storage, data, collection and data transmission facilities have developed so fast and become very cheap, making it possible to apply the techniques of data mining for various purposes. There are many aspects of data mining that have to be considered when writing a degree thesis on data mining.
What is Data Mining?
Raw data does not make any sense until that is organized in some way to show some pattern. With data mining techniques new information can be generated from data. What type of data is used for data mining? A vast amount of data is collected by the computers and computer networks in industry and business, For a supermarket chain point of sales data can be used to generate lot of information that maybe helpful in forecasting trends and correlating buying patterns. In healthcare, the data is collected at hospital admittance points. Though it was the practice to discard the raw data keeping the summaries, now these data have become a goldmine to be mined with data mining techniques. This has become possible with the newest algorithms, software and parallel processing.

universite libre de bruxelles
keys studies data mining tourism
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Data Mining Thesis Topics
When required to write a Data Mining Thesis you have to select an interesting topic that deals with a specific area of the subject. Here are some thesis ideas you can consider for your thesis.
• Data mining applications in marketing: Here students can select one specific use e.g. market segmentation, customer behavior prediction, getting higher response rates in direct marketing, fraud detection, Buyer’s basket analysis and tend analysis.
• Data mining techniques used in scientific research like Weather Forecasting.
• Application of data mining in healthcare — for national health ministry usage as well as for trend analysis in deceases, for development of medications, capacity building in health care etc.
• Data mining used for prevention of Terrorism

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American Literture Dissertation Topics
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Duration : 0:1:55

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IOM 528 – Data Warehousing Business Intelligence, and Data Mining (3 units)

November 28th, 2011 No comments

This course helps to build Business Analytics skill set required by companies. At least sixty percent of the class time is spent on data mining which is especially useful to companies, because it allows you to understand customers to a level not possible before. This course is about how companies apply two new technologies, data warehousing (DW) and data mining (DM, including business intelligence, BI) to empower their employees, and build and manage a customer-centric business model. Besides learning the strategic role DW and DM plays in an enterprise, you will also get a close-up look at DW and DM by working on cases and gaining hands-on experience using software tools. Students taking this class will get an overview of the technologies of DW and BI/DM from a managerial perspective. Finance companies have started data mining, example: Capital One Credit Card Company. Real Estate companies are now using neural networks to evaluate the price of homes.

Duration : 0:3:36

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Quiterian Visual Data Mining helps +100 leading companies to earn money

November 19th, 2011 1 comment

In a dynamic, rapid, changing-world companies need something more than Reporting and Dashboards to compete.

Business users need to react instantly, no waiting, no dependencies on experts.

Better decisions require better insights of customer behavior and business keys.

Only Advanced Analytics reveal us relationships, opportunities and threats that are not evident with traditional BI tools. Visual Data Mining techniques of Quiterian allow non-technical users analyze raw data to obtain immediate key business insights in an intuitive, fast and self-service way.

Users need to know instantly opportunities to sell more, to be more efficient, to predict customer behavior being able to react earlier.

User-friendly, powerful and intuitive Data Mining techniques of Quiterian provide the advanced knowledge that business users need to be more efficient, more effective and more agile.

See how Quiterian helps over 100 leading companies in different industries and how can help you to be more competitive.

Duration : 0:2:11

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Logistic Regression: Part 2 ("Data Mining for Business Intelligence")

November 11th, 2011 No comments

On odds, probabilities, and the logit function

Duration : 0:8:7

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