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 data mining modeling techniques


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 modeling techniques  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.

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Software Functionality Revealed in Detail

We’ve opened the hood on every major category of enterprise software. Learn about thousands of features and functions, and how enterprise software really works.

Get free sample report
Compare Software Solutions

Visit the TEC store to compare leading software by functionality, so that you can make accurate and informed software purchasing decisions.

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Documents related to » data mining modeling techniques

Statistica


StatSoft's flagship product line is the STATISTICA suite of analytics software products and solutions. STATISTICA provides the most comprehensive array of data analysis, data management, data visualization, and data mining procedures. Its techniques include the widest selection of predictive modeling, clustering, classification, and exploratory techniques in one software platform.  

data mining modeling techniques  management, data visualization, and data mining procedures. Its techniques include the widest selection of predictive modeling, clustering, classification, and exploratory techniques in one software platform. Read More

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 analytics is emerging as a distinct new software sector.

data mining modeling techniques  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 fu Read More

Analyse This


Enterprise applications have long been providing the means for businesses to collect required data and deliver it to the right people. Now that sales and marketing professionals are empowered with the right tools to better serve their customers and gather insights on all customers' interactions, the question to ask is what's next? We see the answer in a tight integration between Enterprise applications and Analytics.

data mining modeling techniques  business process performance. However, data mining technology, which focuses on identifying interesting patterns and developing predictive models from data, has the greatest potential for enabling businesses to leverage data resources for strategic business success. Analytical applications are more and more leveraging faster processing speeds, more complex algorithms, and existing data mining infrastructures to help enterprises navigate through their unknown market. The analytics software market has a wid Read More

Predictive Analytics and the Evolution of BI


In the last couple of years, the popularity of predictive analytics offerings has increased significantly, as many companies looking to improve their existing business intelligence (BI) and analytics faculties are looking to the field of predictive analysis to enhance these capabilities, and in some cases even replace them. But, is predictive analysis really the new BI? Is it a replacement for the

data mining modeling techniques  predictive analysis and overall data mining techniques are often the basis for many more specific types of business analytics tools, such as specialized industry and line-of-business analysis tools. Predictive Analysis Is Not BI Business intelligence applications comprise another set of tools for the analysis of historical information as well, and nowadays increasingly use real-time data to perform a different type of data analysis, such as enabling reporting and dashboarding operations or enabling data Read More

DynaFlow Modeling & Workflow Solutions


DynaFlow Modeling and Workflow Solutions Inc., founded in 1997, focusses on the domains of enterprise modeling, workflow management, and knowledge management, in relation to business re-engineering initiatives and ERP implementations. DynaFlow's mission is to support total process management solutions such as Baan-DEM, target enterprise methodology, and its own EZ-Process product suite. Additionallly, DynaFlow focusses on modeling with respect to projects related to ERP, B2B and B2C, and ISO. DynaFlow is based in Quebec, Canada.

data mining modeling techniques  Baan,business process improvement tool,business process reengineering,business processes automation,DEM,dynaflow,dynaflow com,ERP,ISO,knowledge,modeling,process,quality,SOX,workflow Read More

Garbage in, Garbage out: Getting Good Data out of Your BI Systems


Find out in Garbage In, Garbage Out: Getting Good Data Out of Your BI Systems.

data mining modeling techniques  Garbage out: Getting Good Data out of Your BI Systems Garbage in, garbage out. Poor quality data leads to bad business decisions. You need high quality data in your business intelligence (BI) system to facilitate effective analysis—to make the right decisions at the right time. But how do you achieve this? Find out in Garbage In, Garbage Out: Getting Good Data Out of Your BI Systems . In this Focus Brief , you'll learn about the steps in the data delivery cycle, the problems can occur at each step, Read More

Increasing Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management


Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.

data mining modeling techniques  the Supply Chain-Focusing on Data Quality and Master Data Management Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset. Read More

A Roadmap to Data Migration Success


Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources, to a new target database. Effective planning and scoping can help you address the associated challenges and minimize risk for errors. This paper provides insights into what issues are unique to data migration projects and to offer advice on how to best approach them.

data mining modeling techniques  Roadmap to Data Migration Success Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources, to a new target database. Effective planning and scoping can help you address the associated challenges and minimize risk for errors. This paper provides insights into what issues are unique to data migration projects and to offer advice on how to best approach them. Read More

Containerized Power and Cooling Modules for Data Centers


Standardized, pre-assembled, and integrated data center facility power and cooling modules are at least 60% faster to deploy, and provide a first cost savings of 13% or more compared with traditional data center power and cooling infrastructure. Facility modules, also referred to in the data center industry as containerized power and cooling plants, allow data center designers to shift their thinking from a customized “construction” mentality to a standardized “site integration” mentality. This white paper compares the cost of both scenarios, presents the advantages and disadvantages of each, and identifies which environments can best leverage the facility module approach.

data mining modeling techniques  and Cooling Modules for Data Centers Standardized, pre-assembled, and integrated data center facility power and cooling modules are at least 60% faster to deploy, and provide a first cost savings of 13% or more compared with traditional data center power and cooling infrastructure. Facility modules, also referred to in the data center industry as containerized power and cooling plants, allow data center designers to shift their thinking from a customized “construction” mentality to a standardized “s Read More

Re-think Data Integration: Delivering Agile BI Systems with Data Virtualization


Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as productivity improvement and systems as well as data in the cloud. This white paper describes a lean form of on-demand data integration technology called data virtualization, and shows you how deploying data virtualization results in BI systems with simpler and more agile architectures that can confront the new challenges much easier.

data mining modeling techniques  think Data Integration: Delivering Agile BI Systems with Data Virtualization Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as productivity improvement and systems as well as data in the cloud. This white paper describes a lean form of on-demand data integration technology called data virtualization, and shows you how deploying data virtualization results in BI systems with simpler and more 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 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 Data can be a Big Deal - read this white paper for some useful tips on ensuring secure, quality data acquisition and management.

data mining modeling techniques  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

Big Data Comes of Age: Shifting to a Real-time Data Platform


New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose-built platforms more capable of meeting the real-time needs of more demanding end users and the opportunities presented by big data. Read this white paper to learn more about the significant strategy shifts underway to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support big data and the real-time needs of innovative companies.

data mining modeling techniques  Data Comes of Age: Shifting to a Real-time Data Platform New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose-built platforms more capable of meeting the real-time needs of more demanding end users and the opportunities presented by big data. Read this white paper to learn more about the significant strategy shifts underway to transform traditional data ecosystems by creating a Read More

Flexible Customer Data Integration Solution Adapts to Your Business Needs


Siperian's master data management and customer data integration (CDI) solutions allow organizations to consolidate, manage, and customize customer-related data. The type of CDI hub implemented depends on the CDI environment's maturity, requirements, and alignment with an organization's internal processes.

data mining modeling techniques  Customer Data Integration Solution Adapts to Your Business Needs Customer data integration (CDI) has become one of the buzzwords within the master data management (MDM) industry. Although the concept of creating a single organizational view of the customer is noble and desirable, its value should also be justified by organizations. To implement a customer data hub that only creates a centralized view of an organization's customer-related data does not affect a company's bottom line, unless Read More