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SAS Insights Articles
- Stopping the Zika virus: The potential of big data, analytics
- #Data4Good: Treating cancer, one patient at a time
- *Insights Article Quick Start Page - WITH VIDEO
- 10 design elements to consider before building an analytical model
- 10 tips for analytics success
- 10 ways analytics can make your city smarter
- 2018年技術趨勢的兩大共性
- 2019 金融業數位轉型趨勢：使用 ML 技術打擊金融詐騙
- 2021年，台灣製造業如何靠AI繼續逆風高飛？
- 3 things you need to know about event stream processing
- 3 ways to rethink retail forecasting and demand planning
- 4 strategies that will change your approach to fraud detection
- 5 Challenges for IoT in the insurance industry
- 5 data management best practices to help you do data right
- 5 IoT applications retailers are using today
- 5 leadership tips from a four-star general
- 5 machine learning mistakes and how to avoid them
- 5 questions about open analytics
- 5 steps to sustainable GDPR compliance
- 5 ways data monetization can inform data strategy
- 5 ways to measure beehive health with analytics and hive-streaming data
- 6 ways big data analytics can improve insurance claims data processing
- 8 ways an enterprise data strategy enables big data analytics
- 9 questions on in-memory analytics
- 9.2萬洗腎病患，如何用AI即時預判心臟衰竭救命？
- [全台供應鏈調查 – 上] 2022年市場持續動盪，企業如何預測客戶需求做好避震？
- [全台供應鏈調查 – 下] 2022年市場持續動盪，企業如何預測客戶需求做好避震？
- A brave new world of analytics
- A culture of evidence
- A data scientist’s views on data literacy
- A framework for analytics governance
- A Getting Started With Hadoop Checklist
- A guide to machine learning algorithms and their applications
- A lesson in customer service from Chick-fil-A President Dan Cathy
- Analytics for commodity market compliance
- A police force of our time
- AI in banking: Survey reveals factors for success
- AI in government: The path to adoption and deployment
- AI in manufacturing: New opportunities for IT and operations
- AI marketing: What does the future hold?
- AI 劃時代下的商業整合模式，企業如何淬鍊資料新價值贏在數位生態？
- AI 大規模應用的關鍵：ModelOps 打造「生生流轉」模型生態系
- AI 導入起手式！企業該具備的原則與策略是什麼？
- AI 行銷新星 『強化學習』將引領超級個人化行銷的時代
- AI如何改寫保險業機遇？迎向2030年保險業未來趨勢
- AI時代最性感、有趣的職業？SAS台灣資料科學家工作心法大解密！
- Amplify your data career with analytics
- Amplify your data career with analytics
- An executive’s guide to cognitive computing
- Analytic simulations: Using big data to protect the tiniest patients
- Analytics at the edge
- Analytics drives innovation
- Analytics enable companies to provide superior customer experience in telco business
- Analytics for all, all in one place
- Analytics for prescription drug monitoring: How to better identify opioid abuse
- Analytics leads to lifesaving cancer therapies
- Analytics startup focuses on health care optimization
- Analytics tackles the scourge of human trafficking
- Analytics: A must-have tool for leading the fight on prescription and illicit drug addiction
- Applying machine learning to IoT data
- Applying technology to ensure voter integrity in elections
- Are you covering who you think you’re covering?
- Are you good at scoring?
- Are you ready for your smart car?
- Artificial intelligence, machine learning, deep learning and more
- As AI accelerates, focus on 'road' conditions
- BCBS 239: More questions than answers?
- Become a strategic business partner using analytics in finance
- Better alignment of incentives: Helping cure data analytics in health care
- Beyond IFRS 17 – what's next?
- Big data and global development
- Big data and the Internet of Things: Two sides of the same coin?
- Big data in government: How data and analytics power public programs
- Big data in health care
- Big data integration: Go beyond 'just add data'
- 5 things you need to know about big data management
- Big data privacy: Four ways a data governance strategy affects security, privacy and trust
- Big data, big value … huge opportunity
- Brand equity has a big role in RCI's strategy
- Break stuff . . . servers, rules and the glass ceiling
- Bringing data to the stream
- Broken promises? Avoid IoT traps with an analytics platform
- Can advanced analytics for credit scoring change the mortgage market?
- Can data sharing lead to cancer discoveries?
- Canada Post on the (careful) commercialization of data
- Charlie Brown's Teacher Speaks Hadoop. Do you?
- Chief data officer role shakes up traditional data governance
- Clear-cut big data strategy tied to strong financial performance
- Coming soon: The Industrial Internet and IoT standards
- Components of an information management strategy
- Concussion: Journalist crunches the numbers and breaks a scandal
- confidence in your customer experience
- Connected vehicles: IoT steers a new direction for OEMs
- Contact tracing investigations for public health: Technology enhances epidemic investigation
- Containing health care costs: Analytics paves the way to payment integrity
- Contextual engagement
- Continuous monitoring: Stop procurement fraud, waste and abuse now
- Could APIs provide advanced analytics for the masses?
- Credit risk management is the answer
- Customer data platform: What it is and why it’s important
- Customer journey analytics goes mainstream
- Customer journey management: Eliminating missed opportunities
- Customer journeys: How to be ready when customers visit
- Customer loyalty in a digital world
- Customer segmentation for a new digital experience
- Data and the customer experience
- Data drives destiny
- Data governance framework: What is it and do I already have one?
- Data governance: The case for self-validation
- Data integration: It ain't what it used to be
- Data lake and data warehouse – know the difference
- Data lineage: Making artificial intelligence smarter
- Data management backgrounder
- Data quality management What you need to know
- Data quality: The Achilles' heel of risk management
- Data visualization: A wise investment in your big data future
- Data-driven health care | SAS
- Detect and prevent banking application fraud
- Detecting health care claims fraud
- Digital transformation for SMBs
- The digitization of everything — its impact on customer experience
- The digitization of everything – its impact on the buyer’s journey and marketing’s role
- Do marketers need real-time analytics
- Doing good with data
- Edge computing
- Educating informed “intuitants"
- Effective real-time marketing
- Empty shelves: the retail analytical talent deficit
- Establishing a roadmap for government data analytics takes less time than you think
- Exploring the sun with big data
- Finding COVID-19 answers with data and analytics
- Five questions to help bridge the analytics gap
- Five steps that can save your data analytics – and help you save face
- Five trends that will reshape customer experience
- Five ways to approach analytics differently
- Five ways your organization can enhance resilience for years to come
- Four multichannel marketing strategies that deliver exceptional customer experiences
- Fraud detection and machine learning: What you need to know
- From Apollo to AI: A new era of American exploration
- From lab to life
- From living on the streets to owning a profitable business
- frtb: a wait and see strategy could be risky
- Game-changing technologies turn IIoT data into gold
- GDPR and AI: Friends, foes or something in between?
- General Data Protection Regulation: From burden to opportunity
- Goooooal! How data stewards score with data visualization
- Hadoop in the boardroom?
- Hadoop is the new boardroom buzzword
- Hadoop survey results reveal use cases, needs and trends
- Harnessing the martech advantage
- Health care cost containment through big data analytics
- Hiring? We have the data scientist interview questions you need
- Homelessness data holds insights to a hidden problem
- How AI and advanced analytics are impacting the financial services industry
- How big data analytics can be the difference for law enforcement
- How data visualization helps crack down on crime
- How do recommendation systems know what you might like?
- How do you know if you’re ready for Hadoop?
- How does a center of excellence really work?
- How health care leaders deployed analytics when crisis hit
- How openness can supercharge event stream analytics
- How police forces can use data to prevent crime
- How researchers are fighting cancer with analytics
- How to add analytics to your application development pipeline
- How to create your own organizational think tank
- How to drill a better hole with analytics
- How to find and equip the citizen data scientists in your midst
- How to get the most value from your data scientists
- How to improve data prep for analytics: TDWI shares best practices
- How to improve your AI marketing skills
- How to prevent procurement fraud
- How to uncover common point of purchase
- How to work like a disrupter
- How Walmart makes data work for its customers
- Big Data is the Cineplex of Today's Data
- IFRS 17 and Solvency II: Insurance regulation meets insurance accounting standards
- IFRS 17: Waiting is not an option
- IFRS 9 and CECL: The challenges of loss accounting standards
- Improve child welfare through analytics
- Inside sports analytics: 10 lessons for business leaders
- Intelligence for action
- Intelligence for action
- Internet of things applications across multiple industries
- Introduction to machine learning: Five things the quants wish we knew
- IoT challenges in the connected supply chain
- IoT in health care: Unlocking true, value-based care
- IoT in manufacturing: Voices from the field
- IoT success depends on data governance, security and privacy
- IoT: The customer experience accelerator you can't afford to ignore
- IoT: The next best thing to reading your customer’s mind
- Is your data too big to visualize?
- IT/OT convergence: The dilemma of the IoT perception gap
- Keeping an open mind about open analytics
- Key questions to kick off your data analytics projects
- Know your blind spots in tax fraud prevention
- Know your data, know your customers
- Learning the art of analytical storytelling
- Lessons from the track
- Linking data to the customer journey
- Location analytics: Why adding where makes BI better
- Location intelligence: Adding geospatial context to BI
- Machine learning and artificial intelligence in a brave new world
- Machine learning for beginners and beyond
- Major League Soccer Wins Fans with Analytics
- Making sense of streaming data in the Internet of Things
- Managing fraud risk: 10 trends you need to watch
- Marketers and privacy
- Marketing for the midmarket
- Marketing measurement do's and don'ts
- Marketing optimization: Five lessons learned at a major US bank
- Medicaid and benefit fraud in 2018 and beyond
- Meet the data scientist: Alex Herrington
- Meet the data scientist: Colin Nugteren
- Meet the data scientist: Daymond Ling
- Meet the data scientist: Kristin Carney
- Meet the data scientist: Manuel David Garcia
- Meet the data scientist: Steve Einbender
- Meet the data scientist: Victor Fang
- Mobile payments, smurfs and emerging threats
- Model risk management: Vital to regulatory and business sustainability
- ModelOps: How to operationalize the model life cycle
- Modern manufacturing's triple play: Digital twins, analytics & IoT
- Modernize your approach to big data
- Nerd in the herd: protecting elephants with data science
- New attitudes for liquidity risk management
- New payments frontier opens door for more effective health care fraud prevention
- Online fraud: Increased threats in a real-time world
- Online payment fraud stops here
- Operationalizing analytics: 4 ways banks are conquering the infamous ‘last mile’
- Optimizing well placement to eliminate water poverty
- Out of size, out of mind
- Payment fraud evolves fast – can we stay ahead?
- People analytics: Make smarter decisions
- Personal data: Getting it right with GDPR
- Practical advice for better business forecasting
- Preparing a new generation for leadership in a big data world
- Proactive detection – A new approach to counter terror
- Public health infrastructure desperately needs modernization
- Putting an end to pay and chase
- Putting you at the frontier of the fan experience
- R 'Ray' Wang: A conversation with a digital disruptor
- Real-time customer engagement is the future of experience management
- Real-world techniques for analyzing big data
- Reimagine marketing: Today, tomorrow and in times of disruption
- Resilience in the face of unpredictability
- Retail cyber risk tolerance
- Rethink customer due diligence
- Risk capital and lessons from the Titanic
- Risk data aggregation: Transparency, controls and governance are needed for data quality and reporting
- Risk data infrastructure: Staying afloat on the regulatory flood
- SAS CIO: Why leaders must cultivate curiosity in 2021
- Saving lives during a global pandemic through medical resource optimization
- Scenario stress testing: Beyond regulatory compliance
- See IoT industry examples in action
- Sensing a disturbance in the data
- Seven characteristics of the modern consumer
- Seven tips for creating a self-service BI governance strategy
- Should banks adopt regulations as best practices?
- Shut the front door on insurance application fraud!
- Situational awareness guides our responses – routine to crisis
- Skip the fire drills
- Small but mighty: Modern marketing for the midmarket
- Smart cities, smart energy solutions – thanks to the IoT
- Soccer versus baseball: which is the best analogy for data governance?
- Stop contract and procurement fraud
- Streaming data: The ins and outs of this technology buzzword
- Strengthen your payment fraud defenses with stronger authentication
- Student growth measures show the way to educational success
- Student lands dream job with help from SAS
- Supporting indigenous communities with analytics
- Taking pre-emptive action to stem the tide of VAT fraud losses
- The 5 new rules of retail
- The advantages of an analytics culture
- The analytical CRO and the risk aware CFO
- The best gift you can give to thieves this holiday season? Your identity.
- The big effects of big data
- The connected consumer: IoT's impact on the future of retail
- The customer journey: Why you need journey maps
- The era of gargantuan data
- The first step in building a better customer experience
- The five D's of data preparation
- The future of IoT: On the edge
- The Humanity in Artificial Intelligence
- The ideal customer experience on every channel
- The importance of data quality: A sustainable approach
- The intersection of modern IT and advanced analytics
- The marketer's dream: Harmonic convergence
- The modern marketing leader: Is your CMO ready?
- The OODA Loop
- The opportunity of smart grid analytics
- The scoop on Hadoop
- The transformational power of evidence-based decision making in health policy
- The University of Alabama makes better decisions through education analytics
- The untapped potential in unstructured text
- The “problem-solver” approach to data preparation
- Three C’s of the connected customer in the IoT
- Three lessons learned from the model that almost killed Wall Street!
- Three reasons reporting and analytics projects fail and how to avoid the pitfalls
- Three tips for innovating with big data
- Three ways to improve real time marketing results
- Thwarting disruption with strategic investments in innovation
- Tips for hiring and managing data scientists
- Tips for making the most of your analytics software
- Top prepaid card fraud scams
- Tracking down answers to your questions about data scientists
- Tread carefully with customer data platforms
- Turning the analytical talent gap into an analytical talent dividend
- Twelve questions to ask your data visualization software vendor
- Uncover hidden financial crime risk
- Under siege: Improving customer experience in banking
- Understanding capital requirements
- Understanding capital requirements in light of Basel IV
- Understanding data in motion
- Unemployment fraud meets analytics: Battle lines are clearly drawn
- Unlocking the real value of the IoT
- UPS loves logistics … and analytics
- Use education dashboards to publicize the value of analytics
- Use of data visualization and analytics in education is growing
- Using big data to predict suicide risk among Canadian youth
- Using data to change the world
- Using data to control unruly hotel pricing
- Using Hadoop as an analytics catalyst
- Viking transforms its analytics strategy using SAS® Viya® on Azure
- Wanted: AI leaders
- What are AI hallucinations?
- What are chatbots?
- What big data has brought to the privacy discussion
- What coaching a new driver and developing an analytics culture have in common
- What is a data lake & why does it matter?
- What is a risk model?
- What is data profiling and how does it make big data easier?
- What is marketing automation?
- What is omnichannel analytics?
- What is the Internet of Things?
- What was your data doing during the financial crisis?
- What's your level of digital marketing maturity?
- What’s powering the digital economy? The analytics economy.
- When it matters: Safeguarding your organization from the inside
- Which of these 4 types of marketer are you?
- Why banks need to evolve their approach to climate and ESG risk
- Why big data analytics holds the key to tackling the changing terror threat
- Why pharmaceutical firms are investing in real-world evidence
- Why you should care about episode analytics
- Why your brain needs data visualization
- Will health care be fundamentally changed post-COVID-19?
- Winning customers’ hearts (and their feedback)
- Women in analytics: Elisa Gois, MGM Resorts
- Women in analytics: Katherine Sanborn, Kellogg Company
- Women in analytics: Susan Thomas, GM Financial
- Women in Analytics: Susan Weidner, IntrinsiQ Specialty Solutions
- You can’t have that data! It’s not perfect yet
- You don’t know me. Or do you? Data meets anthropology
- Your customers aren't afraid of new technologies. Are you?
- Your personal data scientist
- 「綠天鵝」來了！氣候危機恐致金融危機 全球央行將氣候變遷風險納監管
- 【培養AI「建築思維」擴展篇】共造未來－AI不再是象牙塔，而是每個人的工具箱
- 【培養AI「建築思維」策略篇】打造高可用與可信賴的AI應用：企業AI的「生生流轉」之道
- 【智慧製造新方向】工廠想導入 AI 虛擬量測提升產品良率，在實踐前應注意什麼要點？
- 不用說，我都能懂!「機器學習」給零售業的新解方
- 不用說，我都能懂!「機器學習」給零售業的新解方
- 以 AI 助攻良率提升！SAS台灣攜手貿聯打造智慧製造AI 平台，邁向工業5.0
- 信用卡被盜刷、銀行比你早一步知道？一文看 AI 如何追上快速變化的犯罪者行為！
- 再生能源發展 借力AI少走冤枉路
- 前進工業 5.0 ！SAS 以 AI 智造，打造更高效、更永續的製造業生態
- 升級行銷提升 50% 營收！深化品牌會員經營的「CDP平台」是什麼？
- 半導體供應鏈全球布局：SAS 助力台灣企業強化 AI 數據治理與供應鏈韌性
- 反洗錢大作戰，看AI如何助攻！
- 只有一半 AI 模型具有商業價值？讓 ModelOps 帶你踏上最後一哩路！
- 台灣製造業再戰 10 年新標配：AIoT 如何助力工廠從自動化邁向智慧化
- 哪些政策在PTT被推爆？後疫情時代做這3件事 轉型AI政府正當時
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- 當全球紛紛將 AI 遷徙至雲端，全託管服務如何助攻企業搭上敏捷轉型浪潮？
- 當超前部署成常態，國內醫療體系如何繼續立於不敗?
- 疫後新常態！零售、製造、金融、城市、醫療、教育，哪些趨勢興起？
- 疫情再襲零售業的備戰之道:如何提高需求預測準確度?
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- 疫情期間網路交易大增，全面防護金融詐欺犯罪
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- 薄酒萊如何新鮮準時送到你手中？酒莊用AI預測供需 退貨減80%
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- 資料科學家還在自己做資料清理與特徵工程？怎麼不讓 AutoML 來幫你！
- 資訊超載時代，何不雇個智慧書僮為你擴增溝通力!
- 趨勢觀察／保險業接軌IFRS17 把握數位轉型契機
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Webinars
- 0825event彩排用
- 2019全台企業AI領先度大調查
- AI轉型 - 企業實務應用心法
- Analytics Value Training - A Framework
- Identify, Govern and Protect Personal Data
- Live Webinar
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- MFG-TEST-1
- MFG-TEST-2
- On-Demand Webinar
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- SAS Virtual Insurance Circle
- SAS「啟動資料治理，俱增資料價值」線上研討會
- Trends in Marketing Analytics: Intro to Artificial Intelligence & Machine Learning
- Video Test Clip
- 「建構理專21誡防護網，完備數位金融犯罪防制架構」線上研討會
- 「後疫時代『數位申請』轉型之路」線上分享會
White Papers & E-books
- 5 步驟建構統一的保險決策策略
- AI 與機器學習如何重新定義反洗錢
- AI 藍圖：領導者在快速變革中建立組織信任與提升投資報酬的指南
- CIO 視角
- IFRS 17 的觀點與導入方法
- Make every voice heard with natural language processing
- ModeLops 解說：AI 和分析模型部署與管理入門指南
- SAS® 開源系統
- SAS® 開源系統
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- 五大原因之開發人員遇到生產力瓶頸及其解決之道
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- 人工智慧資料管理
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- 使用進階分析來建模、預測和適應新冠疫情影響下持續變化的消費者行為與需求
- 保險公司：針對 IFRS 17，您準備好了嗎？
- 值得信賴的決策：以可靠的數據與 AI 驅動的策略指南
- 塑造稅務未來的七大趨勢
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- 大規模實現可信任人工智慧與數據驅動決策
- 如何更快實現雲端分析的價值，同時降低成本和風險
- 客戶體驗 2030- 此刻串聯未來
- 將數據轉化為情報
- 建立信任與提升透明度：打擊詐欺，以提升公共計畫效能