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Published By: SAS     Published Date: Aug 27, 2010
Forget spreadsheets. Organizations that are winning in this down economy are using automated analytical tools to take a more scientific approach to decision making through observation, experimentation and measurement to improve their business processes.
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sas, analytics software, business intelligence, data mining, automated analytical tools, computerworld
    
SAS
Published By: SAS     Published Date: Apr 13, 2011
Learn how organizations are using data mining to solve their problems, including a $1 billion decision that produced positive results.
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data mining, qualitative data, quantitative data, john f. elder, data quality, sas, bottom-line
    
SAS
Published By: SAS     Published Date: Apr 13, 2011
This paper will outline the value and methods involved in data mining across both quantitative and qualitative data. In addition, it will describe the data transformations necessary before doing such work, and the tools that are particularly valuable for mining mixed data types.
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business intelligence, michael lock, predictive analytics, business insight, business visibility, small to medium sized business
    
SAS
Published By: SAS     Published Date: Mar 01, 2012
Learn what criteria distinguished certain companies as top performers within the SMB sector, the factors to consider when assessing your organization's BI competency and the required actions to achieve best-in-class performance.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics, it management, ondemand solutions, performance management, risk management, sas® 9.3, supply chain intelligence, sustainability management, business intelligence, michael lock, predictive analytics, business insight, business visibility
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
Stop to think about how - and how often - your business interacts with customers. Most organizations believe that only a small fraction of data on interactions generated are effectively put to use. Why is that? Check out this whitepaper to see.
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sas, voc, voice of customer, visual text analytics, best practices, customer voice, sound of sentiment, text data, customer data, analytical processing, structured data, enriched dataset, reporting, automatic generation, text analytics, text mining, data exploration
    
SAS
Published By: Datawatch     Published Date: Mar 21, 2014
Big Data is not a new problem. Companies have always stored large amounts of data—structured like databases, unstructured like documents—in multiple repositories across the enterprise. The most important aspect of big data is not how big it is, or where it should be stored, or how it should be accessed. It’s the efficacy of business intelligence tools to plumb its depths for patterns and trends, to derive insight from it that will give companies competitive advantage in an increasingly challenging business climate. Visualization allows companies to analyze big data in real-time across a variety of sources in order to make better business decisions.
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visual data discovery, decision making software, data variety, business analysis, data visualization, big data, business analytics, business intelligence, real-time data, real-time data visualization, real-time data discovery, data variety software, data discovery software, data analysis software, data mining tools, data extraction, data reporting, pdf to excel, business reporting, data solutions
    
Datawatch
Published By: IBM     Published Date: Sep 11, 2013
Through this whitepaper from IBM you will learn how to use predictive intelligence to make faster and better decisions
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spss, modeling, data mining, ibm, spss modeler, business analytst
    
IBM
Published By: IBM     Published Date: Nov 14, 2014
Data mining uncovers patterns in data through a variety of predictive techniques. By engaging in data mining, organizations like yours gain greater insight into external conditions, internal processes, your markets – and your customers.
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ibm, data mining, data management, business results, predictive intelligence, business insights
    
IBM
Published By: IBM     Published Date: Nov 14, 2014
IBM® SPSS® Modeler is a powerful, versatile data mining workbench that helps you gain unprecedented insight from your data.
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ibm, data mining, data management, business results, predictive intelligence, business insights
    
IBM
Published By: IBM     Published Date: Feb 19, 2015
Data mining uncovers hidden patterns and relationships in data, driving more informed decisions in organizations of all sizes, and in virtually every industry.
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roi, data mining, big data, business analytics
    
IBM
Published By: Cisco     Published Date: Nov 17, 2014
The desire to invest in antimalware software can be stated simply: avoid malware infection. Malware can create back doors into your network; puts your information, assets, and sensitive intellectual property in peril; and ultimately jeopardizes your business operations, resulting in unspecified collateral damage to your brand. This paper discusses Large-scale data mining technologies, Cloud computing platforms and Deep-seated knowledge of threats facing enterprises.
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cloud-computing, malware, cisco, malware infection, amp
    
Cisco
Published By: IBM     Published Date: Sep 27, 2013
Teams of engineers and statisticians spend their days immersed in seas of data from various sources. However, it isn't just the largest of organizations that can benefit from analytics and data-driven decision-making. Businesses of all sizes need to leverage the new currency of data and information.
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ibm, ibm business analytics solutions, business analytics, analytics solutions, midsize businesses, financial reporting, business intelligence, desktop data visualizations, data mining
    
IBM
Published By: General Atomics     Published Date: Jan 13, 2015
The term “Big Data” has become virtually synonymous with “schema on read” unstructured data analysis and handling techniques like Hadoop. These “schema on read” techniques have been most famously exploited on relatively ephemeral human-readable data like retail trends, twitter sentiment, social network mining, log files, etc.
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general atomics, big data, metadata, nirvana, hadoop
    
General Atomics
Published By: BlueHornet     Published Date: Jun 11, 2008
The effectiveness of your targeting and personalization efforts are only as good as the data used to power them. This article will help you discover effective ways of collecting subscriber data -- allowing you to drive campaigns that evolve as your subscribers' preferences and behaviors change over time.
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blue hornet, bluehornet, data collection, data mining, subscriber information, subscriber, newsletter design, newsletter managment, campaign managment
    
BlueHornet
Published By: SPSS     Published Date: Jun 30, 2009
Read how Cabelcom recognized the key to tackling churn and was able to identify the point at which customers become dissatisfied with their service.
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spss, cablecom, customer retention, crm, churn rate, reduce churn, predictive analytics, statistics, statistical analysis, cable network operator, tailored marketing, targeted marketing, best-of-breed, data mining technology, customer feedback, customer lifecycle, cross-selling, data management, data analysis, decision-making
    
SPSS
Published By: SPSS     Published Date: Jun 30, 2009
The intrepid data miner runs many risks, including being buried under mountains of data or disappearing along with the "mysterious disappearing terabyte."  This article outlines some risks, debunks some myths, and attempts to provide some protective "hard hats" for data miners in the technology sector.
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spss, data mining, data miner, data management, business process, best practices, business intelligence, statistics, statistical modeling, algorithms, predictive analysis, data analysis, scalability, optimization, business knowledge, decision-making
    
SPSS
Published By: SPSS     Published Date: Jun 30, 2009
This paper briefly defines text analytics, describes various approaches to text analytics, and then focuses on the natural language processing techniques used by text analytics solutions.
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spss, text analytics, data management, statistical analysis, natural language processing techniques, computational linguistics, web sites, blogs, wikis, e-mails, instant messaging, predictive analytics, bottom up approach, documents, customer relationship management, crm, voice of the customer, competitive landscape, security threats, understanding text
    
SPSS
Published By: SPSS, Inc.     Published Date: Mar 31, 2009
The intrepid data miner runs many risks, including being buried under mountains of data or disappearing along with the "mysterious disappearing terabyte."  This article outlines some risks, debunks some myths, and attempts to provide some protective "hard hats" for data miners in the marketing sector.
Tags : 
spss, data mining, data miner, data management, business process, best practices, business intelligence, statistics, statistical modeling, algorithms, predictive analysis, data analysis, scalability, optimization, business knowledge, decision-making
    
SPSS, Inc.
Published By: SPSS, Inc.     Published Date: Mar 31, 2009
This paper briefly defines text analytics, describes various approaches to text analytics, and then focuses on the natural language processing techniques used by text analytics solutions.
Tags : 
spss, text analytics, data management, statistical analysis, natural language processing techniques, computational linguistics, web sites, blogs, wikis, e-mails, instant messaging, predictive analytics, bottom up approach, documents, customer relationship management, crm, voice of the customer, competitive landscape, security threats, understanding text
    
SPSS, Inc.
Published By: SPSS, Inc.     Published Date: Mar 31, 2009
Read how Cabelcom recognized the key to tackling churn and was able to identify the point at which customers become dissatisfied with their service.
Tags : 
spss, cablecom, customer retention, crm, churn rate, reduce churn, predictive analytics, statistics, statistical analysis, cable network operator, tailored marketing, targeted marketing, best-of-breed, data mining technology, customer feedback, customer lifecycle, cross-selling, data management, data analysis, decision-making
    
SPSS, Inc.
Published By: SAS     Published Date: Sep 30, 2014
Stop to think about how – and how often – your business interacts with customers. Every day, with each interaction, data is created. What percentage of the data generated by these interactions are you using? There are so many channels for interaction, like social media, call centers, sales staff, help and support resources, marketing and campaigns. Typically, organizations believe that they are using only a small fraction of it effectively – at best, upwards of 10 percent of all the available data. Why? One reason relates to the difficulties in collecting all this data. This limitation is beginning to wane as commodity hardware becomes increasingly popular for big data storage. But another major inhibitor to examining all customer data has been the inability to examine millions, or even billions, of data points that constitute the customer picture. And much of this is now in the form of unstructured text inputs.
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sas, text analysis visualization, voice of the customer, unstructured text inputs
    
SAS
Published By: SpectorSoft     Published Date: Apr 03, 2015
You just got news of yet another issue that just happened in your business that now you need to deal with – it could be a sexual harassment claim, a tip on an employee stealing, or just someone goofing off on the Internet for way too long. Some issues only require the employees involved to get in a room with HR to address, while others require extensive detective work by the good folks in IT. Especially in cases of data theft, fraud, embezzlement, etc., having detail on everything the employee did leading up to the purported “bad deed” will be critical in determining whether something improper occurred or not.
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sexual harrassment, embezzlement, employee investigations
    
SpectorSoft
Published By: IBM     Published Date: May 07, 2015
Hurwitz & Associates announced the findings of its inaugural Victory Index for predictive analytics. This assessment highlights both the diverse uses of predictive analytics and vendors who make those applications.
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predictive analytics, data sources, vendor selection, data mining
    
IBM
Published By: AlienVault     Published Date: Oct 20, 2017
Maintaining Payment Card Industry Data Security Standard (PCI DSS) compliance can be both difficult and expensive. For most small to medium sized organizations, it doesn’t have to be as long as you have the right plan and tools in place. In this paper you’ll learn five steps to implement and maintain PCI DSS compliance at your organization by: • Determining your true business requirements • Inventorying locations and assets • Segmenting environments • Operationalizing controls • Automating controls and control reporting Demonstrating compliance with PCI DSS is far from a trivial exercise. This checklist will help you on your quest to achieve and maintain PCI DSS compliance.
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AlienVault
Published By: Aventail     Published Date: Oct 26, 2007
The goal of pervasive BI applications is to take the data that produced the back office ROI of more than 400% and deliver it to front-line employees in a form appropriate to their job functions – with similar results. There are thousands of business process steps in a typical enterprise where pervasive BI insights can be added. What are leading companies doing with pervasive BI?
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business intelligence, database, enterprise data warehouse, data mart, data warehouse, data mining, active data warehousing, active data warehouse, informatica
    
Aventail
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