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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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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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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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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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How to drill a better hole with analyticsFrom drilling holes to preventing health care fraud, learn about some of the new technologies SAS has patented with IoT and machine learning technologies.
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Five AI TechnologiesDo you know the difference between artificial intelligence and machine learning? And can you explain why computer vision is an AI technology? Find out in this short explainer.
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A guide to machine learning algorithms and their applicationsDo you know the difference between supervised and unsupervised learning? How about the difference between decision trees and forests? Or when to use a support vector algorithm? Get all the answers here.
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Machine learning, Michael J. Fox and finding a cure for Parkinson’sUsing machine learning, data scientists developed a model that can help doctors accurately predict Parkinson's disease progression and start treatment earlier, when it will have greater impact.
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Big data in educationA recent MIT Sloan Management report highlights how businesses are using analytics as a source of innovation – so are universities, says SAS' Georgia Mariani.
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Machine learning and artificial intelligence in a brave new worldWhat is the interplay between man and machine in a brave new world with AI?
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3 steps for AI ethicsWill artificial intelligence benefit humanity or usher in a series of unintended consequences? AI ethics may be one way to ensure artificial intelligence is used for good.
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IoT and machine learning in utilities: What's the difference?The internet of things and machine learning are poised to change the workings of the utilities industry forever, so how are they best defined, what are their revolutionary benefits and what precisely is the difference between the two?
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Meet the data scientist: Kristin CarneyWhen Kristin Carney graduated with a BS in mathematics, she wasn't sure what she wanted to do with her degree. That’s when she began researching data science.
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Meet the data scientist: Daymond LingDaymond Ling believes the right personal traits are more important than technical skills when it comes to being a successful data scientist.
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Meet the data scientist: Colin NugterenData scientist and CAO Colin Nugteren says while every day is different, one thing remains the same. He ends each day with SAS® Visual Analytics.
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Using data to change the worldApplying data science for social good has led to new and creative ways to address issues related to education, poverty, health, human rights, the environment and more.
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4 ways data analytics is changing and benefiting healthcareThe healthcare industry has long been a pioneer in adopting new technology, but how has embracing analytics improved the sector? Let's take a look.
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Big data in real life: The impact of analytics on car manufacturingWant a real-world example of the widespread impact of big data analytics? Look no further than the automotive industry, where modern technology has turbo charged the way information is being collected and used.
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3 data analytics lessons any organisation can learn from top casinosHow can small and medium sized enterprises in Australia and NZ use big data analytics?
First, by learning from major companies already successful in the space, such as casinos.
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5 reasons why everybody should learn data analyticsCould data analytics be the new coding? We certainly think so, and in this article we'll look at five reasons why data analytics is a great skill to learn.
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Keeping an open mind about open analyticsSome of the smartest data science teams are using SAS alongside open source analytics. Find out how you can use both and deploy all models consistently.
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Demand forecasting and the 7 habits of effective retailersWhy do some retailers consistently outperform others? Retail Systems Research reveals some key reasons and offers essential advice for those who want to become (or continue to be) winners.
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Data for good: Protecting consumers from unfair practicesHow text mining and machine learning could help the Consumer Financial Protection Bureau do even more.
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Using analytics to prevent deadly infections Dignity Health’s Bio-Surveillance Program predicts new sepsis cases, allowing early intervention and saving lives.
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Using big data to predict suicide risk among Canadian youthSuicide is the second leading cause of death among youth in Canada. Here's how big data and analytics can be used to help identify at-risk teens.
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Supporting indigenous communities with analyticsThough indigenous women are a small part of Canada's population, they account for a disproportionately large number of Canada's murder victims. Now, big data and analytics are being used to help improve outcomes.
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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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Can analytics and the IoT prevent an energy sector death spiral?Are you hurting your own business by offering enticing deals to new customers?
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Can analytics and the IoT prevent an energy sector death spiral?How does the energy sector develop strategies to effectively leverage opportunities. How can the internet of things (IoT) and analytics save the industry?
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Sending clearer price signals in the energy sector with analyticsPrice signals in the energy sector have significant ramifications that extend far beyond the industry.
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3 issues standing in the way of self-service analyticsA major obstacle blocking self-service analytics is the lack of user-friendliness and flexibility of many analytics tools.
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What’s powering the digital economy? The analytics economy. From the digital economy to the app economy, technology is changing the way we do business and manage resources. Find out how the analytics economy can help you make the most of your data resources.
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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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5 leadership tips from a four-star generalGeneral Michael Hayden, former Director of the CIA, shares what he's learned about managing organizations in times of stress, risk and complexity.
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Five success factors to embed analytics in your organisationAccelerate embedding analytics to drive more from your enterprise analytics investment
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3 capabilities delivered by analytical data visualisationHow is data visualisation set to benefit your organisation? Visual analytics tools from SAS help you understand data faster and more effectively.
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5 questions about open analytics Learn how one analytics team uses a combination of open source and enterprise analytics to find innovative solutions to complex problems.
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How to get the most from your Visual Analytics softwareSAS Visual Analytics is an essential data storytelling platform that local sports organisations can use to manage resources and build participant engagement.
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How to add analytics to your application development pipelineHow can you improve time to market for apps, improve analytics inside apps and let app developers focus on what they do best? With an open analytics platform.
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Student lands dream job with help from SASA strong partnership between the University of Alabama and SAS put Cameron Jagoe on a path that led to his dream job with US Bank.
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How is analytics bringing us the next generation of fan experiences?The fan experience of the future is just around the corner. How are data analytics and smart stadium innovations helping deliver it?
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Banco Galicia launches an analytical journey: Five steps to transforming an organizationBanco Galicia needed to upgrade analytics program to respond to a new business landscape. Learn how SAS helped deliver a strategy to make it work.
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Why analytics is your best ticket vendorGetting fans into the stadium is key for improving revenue from ticket sales. How is SAS Analytics helping teams fill the house on game day?
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Use education dashboards to publicize the value of analyticsHow can education institutions show the effectiveness of their analytics and visualizations? Think about publicizing your key dashboards.
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#Data4Good: Treating cancer, one patient at a timeDrawing on her experience as a cancer patient, Susan Weidner devotes her career to helping oncologists identify personalized treatments based on massive amounts of data.
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The rising star in sports: AnalyticsData analytics is a rising star in sports around the world, helping players and coaches understand and harness the factors that drive success on the field.
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Analytics in the driver’s seat at Ford Ford Chief Data and Analytics Officer Paul Ballew on how Ford is using analytics for everything from sales and marketing to mobility and connected cars.
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Tips for making the most of your analytics softwareEducators need insights from their data. Learn how to harness big data in education using analytics software.
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Women in Analytics: Susan Weidner, IntrinsiQ Specialty SolutionsPractical advice for women interested in pursuing a career in analytics. Mentors were key for Weidner, now a Senior VP at IntrinsiQ Specialty Solutions.
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Lessons learned, looking forwardHow can community colleges train the next generation of skilled workers? Karen Stout, CEO, Achieving the Dream, discusses the role of analytics.
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Best practices to ensure a successful reporting and education analytics initiativeWhat's the best way to get started generating the right information to inform better education decisions? Start with a foundation of education analytics.
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Evolving your institutional insightBig data in education can help administrators understand college applicants and students – including which ones will struggle and why.
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Use of data visualization and analytics in education is growingEducators use analytics for education to make better decisions on programs, student outcomes and more. Learn how you can, too.
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Better alignment of incentives: Helping cure data analytics in health careHealth care organizations are beginning to use analytics to make better decisions. Learn how better incentives can make the process work faster.
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Analytics for all, all in one placeFrom Python to R and SAS to Spark, bring all of your analytics packages together with one trusted platform for analytics governance.
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Practical advice for better business forecastingCheck out three short videos with simple, practical advice for improving business forecasting at your organization.
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Women in analytics: Susan Thomas, GM FinancialWhen Susan Thomas graduated with a technical degree in the 80s, everyone assumed she'd teach. Instead, she became a coder and programmer.
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Could APIs provide advanced analytics for the masses?Find out how APIs could make advanced analytics more prevalent and open up entire new markets to using the predictive capabilities of analytics.
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Five ways to approach analytics differentlyGo beyond the conventional, the insane and the dabbling. Here are 5 ways to rethink how you do analytics.
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Stopping the Zika virus: The potential of big data, analyticsHow do you stop global outbreaks? The answer may be in the data about the disease and how it spreads.
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Stop guessing and try data-driven business decisions insteadHere's some advice from TWDI's David Stodder on how to use visual analytics for data-driven business decisions.
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Data drives destinyUS community colleges need to train 11 million more skilled workers by 2025. Karen Stout, CEO, Achieving the Dream, explains how data can make it happen.
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How to find and equip the citizen data scientists in your midstCitizen data scientists are challenging the status quo and looking at data in new ways. Learn how to recognize, reward and train these analytical minds to benefit the business.
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How Walmart makes data work for its customersTips from the world's largest retailer on building an infrastructure that makes data work for its 240 million customers a week.
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A framework for analytics governanceFind out why governance is the critical last mile for analytics – and learn what you can do to make sure all your analytics projects are accurate, aligned and worthwhile.
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Tips for hiring and managing data scientistsIs it time to hire a data scientist? What skills should you look for? John Taylor leads a team of data scientists and shares his top tips in this short video.
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Holiday shopping secrets: Prices matter and pets are importantAttention retailers! It's time to celebrate. According to SAS Analytics, the holiday shopping season is shaping up to be a jolly one.
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Turning the analytical talent gap into an analytical talent dividendHow important is analytical talent to your organization? If you’re aiming to become data-driven and turn data into insights, make it a top priority.
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Introduction to machine learning: Five things the quants wish we knewMachine learning is gaining momentum thanks to bigger, more complex data sets. How does it work? Kimberly Nevala from SAS Best Practices explains what it is by focusing on what it isn't.
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Top 10 best practices for next-gen analytics TDWI's Fern Halper shares 10 ways to graduate from reports and dashboards and advance to big data visualization and predictive analytics.
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Tracking down answers to your questions about data scientistsDo you need a data scientist? Want to be a data scientist, or improve the skills you already have? Check out our Insights series.
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Meet the data scientist: Steve EinbenderFind out how Steve Einbender lobbied his analytics skills into a data scientist gig at Home Depot and launched the company’s Advanced Analytics Center of Excellence.
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The intersection of modern IT and advanced analyticsThornton May explains how IT groups are helping the business use analytics to adapt to the C-suite's need for a modern, agile and results-focused IT function.
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Hiring? We have the data scientist interview questions you needUse these data scientist interview questions to recruit someone with a range technology skills and a knack for communicating complex subjects to a variety of audiences.
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Meet the data scientist: Victor FangLike many in Silicon Valley, Victor Fang has been a data scientist since before the title was coined. Read this analytical professional's Q&A.
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7 steps for executing a successful data science strategyGet tips from TDWI for making your foray into data science a success.
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Preparing a new generation for leadership in a big data worldWords of wisdom from university leader Dr. Michael Rappa on the role data scientists play, tips for hiring them and how to make the most of this career path.
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Meet the data scientist: Manuel David GarciaWhile he did study statistics, operations research and relational marketing, Data Scientist Manuel-David Garcia's "real school" came from on-the-job-training.
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Best practices report: Business-driven BI and AnalyticsEasy-to-use BI tools are causing business users to bypass IT, but there are pitfalls. Collaboration is needed to make effective use of resources and data says David Stodder in this best practices report from TDWI.
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Meet the data scientist: Alex HerringtonAlex Herrington decided he wanted a career in data because he liked the idea of using numbers to figure out things. Now he’s a data scientist at a US retailer.
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How to get the most value from your data scientistsHiring data scientists isn’t enough. This excerpt from an MIT Sloan report offers advice on how to best manage these analytic professionals.
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Intelligence for actionFind out how three different government agencies are using analytics to deter threats, combat crime and protect the public.
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Intelligence for actionFind out how three different government agencies are using analytics to deter threats, combat crime and protect the public.
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Three reasons reporting and analytics projects fail and how to avoid the pitfallsLearn how to deal with three potential risk areas before you dive into a reporting and analytics project.
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Can sensing cities become thinking and responsive cities?In the vision of the sensing city, sensors will gather data to monitor everything from noise levels to water use, in real time and at a very granular level. Can the resulting data be analyzed to improve the lives of citizens?
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The municipality’s analytical journeyOdense – one of Denmark’s largest municipalities – is working toward becoming more analytical, with a goal of integrating analytical thinking on every level. Learn how their efforts are improving welfare and other programs in the region.
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Data-driven health careLearn how five health care providers are tackling global health issues with big data analytics.
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Inside sports analytics: Ten lessons for business leadersPost "Moneyball" many sports teams take a highly analytical approach to winning, and there are several important lessons that businesses can learn. These 10 tips come from research Thomas H. Davenport conducted on more than 25 professional teams.
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Forecasting in the pocketLearn how to design better forecasting apps for smartphones, tablets and other mobile devices with tips from a renowned user-interface expert.
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Nerd in the herd: protecting elephants with data scienceA passionate SAS data scientist uses machine learning to detect tuberculosis in elephants. Find out how her research can help prevent the spread of the disease.