statistical modeling

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Published By: TIBCO Software     Published Date: Jul 22, 2019
What if you could use just one platform to detect all types of major financial crimes? One platform to handle the analytical tasks of fraud detection, including: Data processing and aggregation Data visualization Statistical/mathematical/machine learning modeling Batch/real-time scoring One platform that could successfully reduce complex and time-consuming fraud investigations by combining extremely different domains of knowledge including Business, Economics, Finance, and Law. A platform that can cover payments, credit card transactions, and know your customer (KYC) processes, as well as similar use cases like anti-money laundering (AML), trade surveillance, and crimes such as insurance claims fraud. Learn more about TIBCO's comprehensive software capabilities behind tackling all these types of fraud in this in depth whitepaper.
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TIBCO Software
Published By: ttec     Published Date: Jul 24, 2019
Let’s face it: in today’s B2B landscape, the buyers call the shots. Buyers today are proactive, research their own options, and often include many decision makers rather than just one who can be wooed on a golf course or over dinner. So, where does that leave the salesperson? To succeed in this new landscape, sales professionals must understand how the buyer’s journey has changed and unlock the advantages that data analytics and statistical modeling can offer. Sales and marketing teams must also learn how to align their efforts to present a truly coordinated experience. Read this paper to learn how to take advantage of untapped opportunities for helping sales teams evolve in today’s buyer-empowered landscape.
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ttec
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, 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.
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