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The Truth about Data Mining
It is now imperative that businesses be prudent. With rising volumes of data, traditional analytical techniques may not be able to discover valuable data

data mining machine learning  Truth about Data Mining A business intelligence (BI) implementation can be considered two-tiered. The first tier comprises standard reporting, ad hoc reporting, multidimensional analysis, dashboards, scorecards, and alerts. The second tier is more commonly found in organizations that have successfully built a mature first tier. Advanced data analysis through predictive modeling and forecasting defines this tier—in other words, data mining. Data mining has a significantly broad reach and application. Read More...
Mining Industry (ERP & CMMS)
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Documents related to » data mining machine learning


Predictive Analytics; the Future of Business Intelligence
Business intelligence (BI) is evolving as it grows in popularity. Within BI, there is a shift from traditional analytics to predictive analytics, and predictive

data mining machine learning  is the branch of data mining concerned with the prediction of future probabilities and trends. Predictive analytics is used to automatically analyze large amounts of data with different variables; it includes clustering, decision trees, market basket analysis, regression modeling, neural nets, genetic algorithms, text mining, hypothesis testing, decision analytics, and more. The core element of predictive analytics is the predictor, a variable that can be measured for an individual or entity to predict Read More...
TEC Industry Watch: Enterprise Software News for the Week of June 11, 2012
SOFTWARE SELECTIONSJeanswest selects Manhattan Associates Industry tags: Fashion/retail

data mining machine learning  find surrogate products via data mining techniques. Then, it uses domain knowledge to fine-tune the surrogate panel of surrogate data based on product segmentation and clustering, to finally use statistical forecasting methods to forecast the new product. Last but not least, SAS DDF comes with a Consensus Forecasting Workbench that uses Microsoft Excel as the interface and uses real workflow to create a consensus forecast based on demand shaping activities. —P.J. Jakovljevic, Principal TEC Analyst TEC Read More...
The Intelligence of Social Media (Part 2)
In the first part of this blog, I mentioned that sentiment analysis measures the polarity of opinion—positive, negative, or neutral—regarding a subject, a

data mining machine learning  sources based on preconfigured data items (people, places, dates, etc.). It can highlight sentence relevance and prepare executive reports based on the content found. •    SPSS Text Analysis for Surveys 3.0 from IBM can help improve text analysis. It enables companies to extract and analyze survey responses. The effort focused on sentiment analysis is customer-oriented, which in turn has more impact on customer relationship management systems (CRMs). This enables more operation related users to be Read More...
Data, Data Everywhere: A Special Report on Managing Information
The quantity of information in the world is soaring. Merely keeping up with, and storing new information is difficult enough. Analyzing it, to spot patterns and

data mining machine learning  online, are masters of data mining (or business intelligence , as it is now known). By analysing basket data , supermarkets can tailor promotions to particular customers' preferences. The oil industry uses supercomputers to trawl seismic data before drilling wells. And astronomers are just as likely to point a software query tool at a digital sky survey as to point a telescope at the stars. There's much further to go. Despite years of effort, law-enforcement and intelligence agencies' databases are Read More...
Data Center Projects: Advantages of Using a Reference Design
It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete

data mining machine learning  aspects of a unique data center. Re-use of proven, documented subsystems or complete designs is a best practice for both new data centers and for upgrades to existing data centers. Adopting a well-conceived reference design can have a positive impact on both the project itself, as well as on the operation of the data center over its lifetime. Reference designs simplify and shorten the planning and implementation process and reduce downtime risks once up and running. In this paper reference designs are Read More...
The Future of Learning: Industry Trends in Learning Management
Learning management systems (LMSs) have evolved over their short history in many ways. From the first classroom-based “training management systems” to today’s e

data mining machine learning   Read More...
Optimizing Gross Margin over Continously Cleansed Data
Imperfect product data can erode your gross margin, frustrate both your customers and your employees, and slow new sales opportunities. The proven safeguards

data mining machine learning  Margin over Continously Cleansed Data Optimizing Gross Margin over Continously Cleansed Data If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Advanced functionality to manage costs, sell prices, promotions, discounts, chargebacks, and other key attributes while optimizing gross profits. Source : epaCUBE Resources Related to Optimizing Gross Margin over Continously Cleansed Data : Data cleansing (Wikipedia) Gross margin (Wikipedia) Read More...
Learning from the BPM Leaders
Find out in the white paper learning from bpm leaders.

data mining machine learning  learning bpm leaders,learning,bpm,leaders,bpm leaders,learning leaders,learning bpm. Read More...
Top Three Learning Management Trends for 2011
Learning management is a growing market in certain geographical areas and within specific industries. The availability of mobile and collaborative learning

data mining machine learning  and LMS solutions. Using data from TEC’s Evaluation Centers, we compiled information about end-user trends (looking first at users by geographic location and then by industry). The percentages in the figures below were derived by taking the total number of end-user inquiries from each location or industry type and dividing that by the total number of users for a given year. If we look at statistics over the past three years, we see a growing interest in learning management in specific geographic Read More...
Considerations for Owning versus Outsourcing Data Center Physical Infrastructure
When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both

data mining machine learning  for Owning versus Outsourcing Data Center Physical Infrastructure When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing; however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash crossover point, deployment timeframe, data center life Read More...
Don't Be Overwhelmed by Big Data
Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect

data mining machine learning  Be Overwhelmed by Big Data Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect of more data that can be used to better understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Big Read More...
The Advantages of Row- and Rack-oriented Cooling Architectures for Data Centers
The traditional room-oriented approach to data center cooling has limitations in next-generation data centers. Next-generation data centers must adapt to

data mining machine learning  Rack-oriented Cooling Architectures for Data Centers The Advantages of Row and Rack-Oriented Cooling Architectures for Data Centers If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. In today's always on, always available world where businesses can't stop and downtime is measured in dollars, American Power Conversion (APC) provides protection against some of the leading causes of downtime, data loss and hardware damage: power problems Read More...
Oracle Database 11g for Data Warehousing and Business Intelligence
Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and

data mining machine learning  Database 11g for Data Warehousing and Business Intelligence Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data. Read More...
Data Quality: A Survival Guide for Marketing
Even with the finest marketing organizations, the success of marketing comes down to the data. Ensuring data quality can be a significant challenge

data mining machine learning  to the data. Ensuring data quality can be a significant challenge, particularly when you have thousands or even millions of prospect records in your CRM system and you are trying to target the right prospect. Data quality, data integration, and other functions of enterprise information management (EIM) are crucial to this endeavor. Read more. Read More...

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