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Fighting coronavirus: 4 ways analytics is making a differenceCoronavirus has separated us from family, friends, cultural and religious communities. Unfortunately, isolation is essential to slowing the spread of the virus. What else can be done? Learn how analytics is being used to improve responses to the coronavirus outbreak.
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Your customers aren’t afraid of new technologies. Are you? New research uncovered some interesting themes for the next decade of customer engagement. Surprisingly, consumers are embracing technology at a faster rate than brands might expect or admit.
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Break stuff . . . servers, rules and the glass ceilingCarla Gentry knows what it’s like to be the only woman on the team and is happy to share her hard-won knowledge with an ever-growing number of female data scientists. She recently shared with us some sage advice for women entering or interested in advancing in the field.
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Tread carefully with customer data platformsThe potential benefits of customer data platforms are significant, but CDPs are by no means a silver bullet. Follow these three steps to avoid disillusionment.
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Managing fraud risk: 10 trends you need to watchSynthetic identities, credit washing and income misrepresentation – these are just some of the trends to watch if you’re trying to understand how to manage fraud risk. Find out what’s on the top 10 list of trends according to experts like Frank McKenna and Mary Ann Miller.
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Continuous monitoring: Stop procurement fraud, waste and abuse nowProcurement fraud, waste and abuse silently robs businesses an average of 5% of spend annually. And even when organizations invest in detection methods, they’re often let down by their techniques. Learn what continuous monitoring is and why this proven analytical method is key to fighting back.
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Marketers and privacyCompanies that break new privacy laws get fined heavily, but there may be an even greater cost: A damaged reputation.
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Analytics leads to lifesaving cancer therapiesA long-shot treatment offers hope to 10-year-old Harrison after he learns the DNA profile of his cancer is resistant to chemo. Find out how data and analytics play a role in cancer research and cancer treatments that are saving lives.
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How to work like a disrupterFind out what companies like Netflix, Airbnb, Spotify and Lyft know about analytics that you don't know. Learn how to become technologically and analytically mature just like them.
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5 data management best practices to help you do data rightFollow these 5 data management best practices to make sure your business data gives you great results from analytics.
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Digital transformation for SMBsFor small and midsize businesses, delivering a better. customer experience is key to digital transformation
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Three steps for conquering the last mile of analyticsPutting your analytical models into production can be the most difficult part of the analytics journey. It’s no surprise that this last mile of analytics – bringing models into deployment – is the hardest part of digital transformation initiatives for organizations to master, yet it’s the most crucial.
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Discover a secret resource for working with cloud providersAre you overwhelmed by the hundreds of options and offers in the cloud? Are you finding it hard to select the best cloud services from the different cloud providers? Why not ask a neutral and informed third party for help?
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As AI accelerates, focus on 'road' conditionsAI technology has made huge strides in a short amount of time and is ready for broader adoption. But as organizations accelerate their AI efforts, they need to take extra care, because as any police officer will tell you, even small potholes can cause problems for vehicles traveling at high speeds.
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The transformational power of evidence-based decision making in health policyState health agencies are under pressure to deliver better health outcomes while minimizing costs. Read how data and analytics are being used to confront our biggest health care challenges head on.
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Operationalizing analytics: 4 ways banks are conquering the infamous ‘last mile’Here are four examples across the banking industry that show how these leading organizations followed a clearly defined path to conquer the infamous 'last mile' of analytics.
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ModelOps: How to operationalize the model life cycleModelOps is where analytical models are cycled from the data science team to the IT production team in a regular cadence of deployment and updates. In the race to realizing value from AI models, it’s a winning ingredient that only a few companies are using.
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AI in government: The path to adoption and deploymentThe government sector is lagging in AI adoption, but awareness of the importance of AI in the public sector is increasing. Our survey indicates that operational issues are requiring governments to turn their attention to AI projects as a way to address important public issues.
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Five trends that will reshape customer experienceApplying the latest research from HBR gives a new twist on this surprisingly relevant 2015 list of CX do’s and don’ts.
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Under siege: Improving customer experience in bankingBanks are ranking low in customer satisfaction, but improvement is possible says Digital Banking Report owner and publisher Jim Marous.
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From Apollo to AI: A new era of American explorationAs we celebrate the 50th anniversary of the Apollo 11 mission, what’s the next frontier for American Innovation? It’s available now, from our desks and waits for us to unlock its potential.
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Next generation anti-money laundering: robotics, semantic analysis and AIAnti-money laundering taken to its next level is sometimes referred to as AML 2.0 or AML 3.0. What does this next wave of AML technology look like? What can it do that you can’t do with traditional AML? See the results innovative financial institutions around the globe are already getting.
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The untapped potential in unstructured textText is the largest human-generated data source. It grows every day as we post on social media, interact with chatbots and digital assistants, send emails, conduct business online, generate reports and essentially document our daily thoughts and activities using computers and mobile devices.
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AI in manufacturing: New opportunities for IT and operationsAn AI survey reveals that leaders and early adopters in AI are making important advances and are identifying and expanding on what works as they use AI in more ways and more parts of their organizations.
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The Humanity in Artificial IntelligenceCould artificial intelligence be the change agent we need to solve many problems around the globe? Read how AI could accelerate our ability to have a a positive, lasting impact.
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The state of insurance fraud technologyA 2019 Coalition Against Insurance Fraud study surveyed 84 companies on their use of anti-fraud technologies and compared results to 2014 and 2016. Get the highlights here.
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Edge computingWith traditional methods, data is captured, stored and analyzed later – limiting how quickly businesses can act on insights from the data. With edge computing, IoT data is processed at the edge of a network – right where it’s created or collected – avoiding delays and enabling real-time processing and action.
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How AI and advanced analytics are impacting the financial services industryTop SAS experts weigh in on the topics that are keeping institutions up at night and fraudsters in a job.
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AI in banking: Survey reveals factors for successWhat do banking executives report about their experiences with AI? Where are they focusing today? What’s working? What are their plans for the future?
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What are chatbots?Chatbots are a form of conversational AI designed to simplify human interaction with computers. Learn how chatbots are used in business and how they can be incorporated into analytics applications.
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IoT: The customer experience accelerator you can't afford to ignoreIoT represents a powerful source of data that, when combined with analytics, can yield insights on everything from behavior to emotions to health. And that's why it's key to improving customer experience.
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Data lineage: Making artificial intelligence smarterFor AI to reach its full potential, the data feeding its algorithms and models needs to be well-understood. Data lineage plays a vital role in understanding data, making it a foundational principle of AI.
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