Analytics
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Machine learning for beginners and beyondWhether you’re an experienced data scientist or a machine learning beginner, you’ll appreciate these 10 tips for getting started with machine learning.
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What is omnichannel analytics?Omnichannel analytics used to mean recognizing and marketing to customers across all channels. Now, smart retailers know it can, and must, mean so much more.
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Concussion: Journalist crunches the numbers and breaks a scandalHow Pulitzer Prize-nominated journalist Alan Schwarz used his stats background to achieve the most remarkable feat in sports journalism history.
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Interview
The University of Alabama makes better decisions through education analyticsAt the University of Alabama, the Office of Institutional Research and Assessments use analytics and data visualizations to uncover better student outcomes.
Big Data
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How do free-to-play video games earn big profits?How does the industry leader of free-to-play, massively multiplayer online games scale its customer intelligence and analytics efforts to thousands of models and terabytes of data a day? With industrialized modeling from SAS.
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5 machine learning mistakes and how to avoid themMachine learning is not magic. It presents many of the same challenges as other analytics methods. Learn how to overcome those challenges and incorporate this technique into your analytics strategy.
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Can data sharing help cure cancer?Clinical trials can bring new drugs – and new hope – to the market for cancer patients. Now, a new data sharing platform for clinical trial data brings even more hope.
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Article
Becoming CognitiveCognitive computing is an outgrowth of artificial intelligence, with a healthy dose of big data thrown in.
Business Intelligence
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Interview
Location analytics: Why adding where makes BI betterLearn how location analytics can enrich your BI endeavors by blending geographic data, spatial analysis and business data for deeper insights.
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IIA research identifies barriers to business intelligence and analytics adoptionFind out what the biggest barriers are to business intelligence and analytics adoption and how to overcome them.
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Learning the art of analytical storytellingCrafting and pitching enticing data-driven stories is a vital skill to master. Here are a few tips to help you get started with storytelling visualizations.
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Governed analytics and discovery: Balancing business user and IT needsTDWI provides seven steps for balancing IT governance needs with the expanding use of self-service BI and data discovery tools.
Data for Good
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Concussion: Journalist crunches the numbers and breaks a scandalHow Pulitzer Prize-nominated journalist Alan Schwarz used his stats background to achieve the most remarkable feat in sports journalism history.
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Article
Analytics tackles the scourge of human traffickingVictims of human trafficking are largely invisible. And they're all around us. Now organizations are applying analytics to combat the problem -- and are achieving initial success.
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Can data sharing help cure cancer?Clinical trials can bring new drugs – and new hope – to the market for cancer patients. Now, a new data sharing platform for clinical trial data brings even more hope.
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Article
Analytic simulations: Using big data to protect the tiniest patientsAnalytic models help researchers discover the best way to care for babies in the NICU, saving lives (and millions of dollars) in the process.
Data Management
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Data quality management What you need to knowData quality isn’t simply good or bad. Data quality management puts quality in context to improve fitness of the data you use for analysis and decision-making.
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The future of IoT: On the edgeFrom cows to factory floors, the IoT promises intriguing opportunities for business. Find out how three experts envision the future of IoT.
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Data lake and data warehouse – know the differenceData lake – is it just marketing hype or a new name for a data warehouse? Find out what a data lake is, how it works and when you might need one.
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What is data profiling and how does it make big data easier?Data profiling, the act of monitoring and cleansing data, is an important tool organizations can use to make better data decisions.
Fraud & Security
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Stop contract and procurement fraudFraud affects an estimated 30 percent of organizations' procurement processes. Beyond business rules and anomaly detection, analytics can detect and prevent fraud and preserve the integrity of the procurement process.
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Uncover hidden financial crime riskEscalating threats call for a financial crime risk framework that uses powerful, visual, interactive techniques to proactively identify hidden risks.
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A lifecycle approach to security analyticsThe January 2017 Ponemon Institute report on security analytics is a call to action to take a more holistic and systematic lifecycle approach to get the results organizations are expecting.
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Know your blind spots in tax fraud preventionWhat can tax agencies do differently today than just a few years ago? Find out where fraud may lurk inside your agency – and the role analytics can play in tax fraud prevention.
Marketing
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What is marketing automation?Marketing automation uses the customer data you collect to create more effective campaigns and for better decisions across all channels – email, social and web.
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Real-time customer engagement is the future of experience managementReal-time customer engagement delivers contextual recommendations and decisions to your interactive customer channels at every possible touch point.
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The marketing analytics must-havesMarketing analytics will attune you to the true signals of what matters to customers as channels, technologies and data push the digital world forward.
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Harnessing the martech advantageMartech vendors have doubled in the past year. Find out what's fueling this growth spurt, and discover three ways to get the most value from your tech spending.
Risk Management
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frtb: a wait and see strategy could be riskyFRTB, fundamental review of the trading book, is a regulation that changes how banks analyze market risk in the trading book to address systemic challenges.
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CECL: Are US banks ready?CECL, current expected credit loss, is an accounting standard that requires US banking institutions to estimate life-of-loan losses at origination or purchase.
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IFRS 17 and Solvency II: Insurance regulation meets insurance accounting standardsIFRS and Solvency II encourage comparability and transparency from a regulatory and accounting perspective for insurers, but there are important differences.
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Credit risk management is the answerLending and loan volume is back up to pre-crisis levels. But banks are facing higher delinquencies as well. That's why improving credit risk management is crucial.