Subscribe to the Teradata Blog

Get the latest industry news, technology trends, and data science insights each week.



テラデータはソリューションやセミナーに関する最新情報をメールにてご案内する場合があります。 なお、お送りするメールにあるリンクからいつでも配信停止できます。 以上をご理解・ご同意いただける場合には「はい」を選択ください。

テラデータはお客様の個人情報を、Teradata Global Privacy Policyに従って適切に管理します。

Yasmeen Ahmad

The Teradata Blog is best viewed with JavaScript enabled.

  1. Building a Roadmap for Enterprise Data and Analytics – A Framework
  2. The Post-Pandemic Supply Chain: How to Build Resiliency Into our Decisioning
  3. Flying Blind in Retail
  4. Teradata's Sleep Prediction Hackathon
  5. The Post-Pandemic Supply Chain: Time to Go Back to Basics?
  6. How to Get More ROI—Faster—From Machine Learning
  7. COVID-19 Pandemic Analytics for a Safe Return-To-Office
  8. Tired of First Dates? How to Build a Long-Term Relationship with Data
  9. Open Finance and Smart Ecosystems Won’t Wait for Banks
  10. Is Your Data Ready for Climate Risk Scrutiny?
  11. Managing Supply Chains in the Fast Lane
  12. What Concept Are You Trying to Prove?
  13. Look Out for Risks in Open Banking!
  14. The Cloud is Just the Beginning, Not the End, of the Journey
  15. The Automation of Personalisation
  16. Three Guiding Principles for Open Banking Platform Design
  17. Connecting R&D to the Digital Thread
  18. Financial Crimes: Three Things You Need to Catch a Clever Criminal
  19. Billions of Personal Interactions
  20. It Just Got a Lot Easier to Offload Data From Vantage to Cloud Storage
  21. Off-shore, On-shore or Not Sure? How Data Can Help Solve the Shared Services Conundrum
  22. Will Open Banking Enhance the Quality of Daily Life?
  23. We Rise as One in our Mission to Eradicate Racism
  24. Why CEOs Must Lead a New Relationship with Data
  25. Listen Carefully
  26. Thirteen Thoughts About the Data Mesh
  27. Data...What? Why You Should Keep Doing Data Integration
  28. Beyond Resilience-The Next Generation of Supply Chain
  29. Open Banking is Transforming Financial Services and Chipping Away the Relevance of Traditional Banks
  30. What Isaac Newton Did in Lockdown – And What it Tells Us About Data Science
  31. The Race to Transform
  32. Making Customer Experience Your Competitive Advantage
  33. CFO Analytics – Machine Learning
  34. Hyper-Personalization: Understanding Customers Using Digital Payments Data
  35. The Worst of Times - The Best of Times
  36. Connect Teradata Vantage to Salesforce Using Amazon Appflow
  37. CFO Analytics - CFO of the Future
  38. Data Mesh and the Threads that Hold it Together
  39. あなたのスマートファクトリーはどれくらいスマート(賢い)ですか?
  40. Meet the New Analytics Superhero - The CFO
  41. Data...What? Data Democratization and the Illusion of Self-Service
  42. CFO Analytics – Driving Value Through Analytics Automation
  43. We Stand as One with Asian American and Pacific Islander Communities
  44. How to Host a Virtual Global Data Science Hackathon
  45. 車両データを収集するだけでなく、収益化しましょう!
  46. Ending Supply Chain Whack-a-Mole Management
  47. CFO Analytics – Build Your Foundation
  48. Streaming Data Into Teradata Vantage Using AWS Glue Streaming ETL
  49. Texas Health Resources
  50. Is There a Better Way to Drive Faster Business Value Without Creating More Technical Debt?
  51. クラウドのエンタープライズデータオペレーティングシステム:必要だが十分ではない
  52. All That Glitters is Not Gold!
  53. Banco Bradesco
  54. The Future: Seamless Journey to Invisible Payments
  55. すべての旅(ジャーニー)でカスタマーエクスペリエンスを向上させる
  56. CFO Analytics: What Is It and Why Should You Care?
  57. Is the Centralized Data Warehouse Dead?
  58. Drive Superior Customer Experience in Retail with Data
  59. Teradata Has Been Named One of the World's Most Ethical Companies 2021
  60. Data Governance in the Cloud Era – Accelerating, Not Hindering, Data Democratization
  61. Machine Learning Adapts to Rapidly Evolving Risk in Real-Time
  62. Is Your Data Holding You Back Instead of Driving You Forward?
  63. 製品サイクルからデジタルスレッドへ
  64. How I Built an Algorithm to Help Doctors Fight COVID-19
  65. Vantage Trial Delights Cloud Data Analytic Users
  66. Digital Payments Analytics Rapidly Respond to Changing Preferences and Emerging Value Propositions
  67. Six Crucial Refinements to Conventional Wisdom About Data Strategy
  68. Modeling the Risk of COVID-19 for Effective Pandemic Response
  69. Big Data in Retail & CPG Requires a Scalpel, Not an Axe
  70. What is the Business Case for Delivering a Good Customer Experience at Your Bank?
  71. How Does UX Design Help in Visualizing Big Data?
  72. Digital Payments Data Drives Increased Usage and Customer Retention
  73. クラウドコストの失ったリンク
  74. Moving to the Cloud, Do I Still Need a CASB Solution?
  75. How to Make Regulatory Calls for Transparency a Competitive Advantage
  76. Drowning in Data - Regulators Need a Data Strategy Too!
  77. Improving Population Health Through Citizen 360
  78. Digital Payments: An Explosion of Emerging Opportunities
  79. クラウドに移行するときに知っておくべきいくつかのこと
  80. The High Stakes of Complex Medical Claims
  81. A Day in the Life of a Customer Success Manager
  82. Regulation as a Service: A Win-Win
  83. Vantage Social Network Analysis Framework for Covid-19 Risk Metrics
  84. Avoid Making the Same Mistake Twice
  85. Top Tech Predictions for 2021
  86. Path to Profitability with More Agile Pricing
  87. Data...What? What Can I Buy in a Data Marketplace?
  88. Looking Forwards Not Backwards: New Ways of Working for the CFO
  89. Medibank
  90. サプライチェーン投資の経済的価値
  91. How Much Security Is Too Much Security?
  92. Data and Strategic Alignment in the Bank of the Future
  93. How to Tackle Data Skew
  94. Teradata at AWS re:Invent
  95. Intertoys
  96. Risk-Based Wealth Management: What the Insurance Industry Gets Wrong
  97. How to Thrive Amid Disruption
  98. Telecom Operators: The Data Goldmine
  99. Is Skepticism Thwarting Your Grandiose AI Plans?
  100. Brinker International, Inc.
  101. What Banks Can Learn From Disney
  102. Getting Started with Native Object Store and Microsoft Azure Object Storage in 5 Easy Steps
  103. How Tesla is Redefining the Auto Industry
  104. How to Make the Most of Big Data Analytics in Your Business
  105. Boost Your Customer Experience with Better Payment Conversions
  106. Connect Teradata Vantage to Salesforce Data With Azure Data Factory
  107. What Happened to the CEO in Waiting?
  108. Reimagining Business Amidst the COVID-19 Pandemic
  109. Reconnecting the Retail Brain: Learning From the Octopus
  110. Look at the Cloud. What Do You See?
  111. Survey: Enterprise Data More Important Than Ever Since Onset of COVID-19
  112. Modern Architecture and Analytics Need Each Other To Succeed
  113. Demystifying the Business Continuity Space: Part 2
  114. Exit Here? The Big Banks' Battle for Survival
  115. Why the Single Source of Truth Paradigm in Data Warehousing is Outdated
  116. Data: The Crumbling Foundation of Finance, Our Once Trusted Advisor
  117. How to Prioritize "Self" in Today's World: A Summary on Mental Health
  118. DHL Express
  119. クラウドデータウェアハウスの価格設定の落とし穴に注意してください
  120. 頭金なし – テラデータの従量課金制で使用した分だけ支払う
  121. Accelerating Innovation in the Analytic Ecosystem: Accessibility
  122. Retailers - Don't be a Data Zombie!
  123. Announcing Vantage on Google Cloud
  124. スマートファクトリー投資から大規模な価値を提供するための3つの洞察
  125. Demystifying the Business Continuity Space: A Two Part Series
  126. Break Out of the Data Silo!
  127. Accelerate Your Path to a Modern Analytics Architecture
  128. Customer Journey Analytics & Real-Time Marketing: Lessons Learned from Those That Got it Right
  129. Five Steps Towards Delivering Better Analytic Outcomes
  130. Today’s ‘Breakfast Roll People’ Will Change How Energy Retail Operates
  131. Celebrating Hispanic Heritage Month
  132. Clean Up Your Enterprise Data Mess the Easy Way: Ignore it
  133. Leveraging Teradata Vantage's Superior Performance for Real-Time Analytics
  134. The Game Has Changed for Retail – or Has it?
  135. Teradata: An Enduring Legacy
  136. To Integrate or Not to Integrate Data? That is the Question.
  137. The Cause and Effect of Supply Chain Fragility, and How to Fix It
  138. How Teradata Vantage with Native Object Store Decreases Costs, Increases Business Value
  139. The Power of Data and Analytic Processing Gravity
  140. Back to school – CEOs need to learn a new language, fast!
  141. Teradata Dynamic Resource Optimization – Both On-Premises and in the Cloud
  142. Larry H Miller Sports & Entertainment
  143. Accelerating Innovation in the Analytic Ecosystem: Simplicity
  144. Will a Few Milliseconds Ruin Your Analytics Performance in the Cloud?
  145. Digitalizing Energy: A Cure-All Salve or Expensive Placebo?
  146. Use of Modeling and Simulation for Understanding COVID-19 Dynamics
  147. So You Think You’ve Got a Data Strategy?
  148. Change for Good: The Energy Transition
  149. Customer Experience During the “New Normal”
  150. Using Data Before, During, and After Natural Disasters
  151. Answers in the Cloud, No Matter Where Your Data Is
  152. Teradata Vantage: Born for Cloud Before Cloud Was Born
  153. Accelerating Innovation in the Analytic Ecosystem: Flexibility
  154. Chief Data Analytics Officers – The Key to Data-Driven Success?
  155. Why Object Storage Is Essential for Analytics
  156. Architecting for Today’s Hybrid Analytic Ecosystem
  157. Move Fast – But Don’t Break Things
  158. Streaming Data Into Teradata Vantage Using Amazon Managed Kafka (MSK) Data Streams and AWS Glue Streaming ETL
  159. Why Teradata Has Never Been Afraid of High Demand
  160. Advancing the Telecom Industry through Network Experience Analytics
  161. I’ve got the latest tech – now I’m a data business, right?
  162. Move Up the (Data) Property-Ladder
  163. Why You Need to Treat Models Like Data
  164. Doing Good With Data: Teradata's COVID-19 Resiliency Dashboard
  165. Streaming Data Into Teradata Vantage using Amazon Kinesis Data Streams (KDS) and AWS Glue Streaming ETL
  166. Forecasting COVID-19 Using Teradata Vantage
  167. The Importance of Data in UX Design
  168. Data...What? Whatever You Call It, Stay Away From a Data Mess!
  169. Return on Data – The New Valuation for Future Retail
  170. That Lockdown Feeling
  171. Teradata Vantage for People Analytics
  172. Native Object Store (NOS)で始めよう
  173. Royal Bank of Canada
  174. What Sort of Business Do You Want to Be?
  175. テラデータは主要なアナリスト調査において高評価を獲得
  176. Announcing Vantage Trial
  177. Identifying the Infodemic Amidst the COVID-19 Pandemic
  178. Data is the Prize and the Strategy
  179. How to Leverage Advanced Analytics in the Healthcare Domain
  180. Big Tech is Poised to Pounce on Banking
  181. モダナイゼーションに必要なのは、シンプルさと高度さ
  182. Microsoft Azureファーストパーティ・サービスとTeradata Vantageの統合
  183. There Are No Perfect Words…
  184. Lloyds Banking Group
  185. AWSファーストパーティ・サービスとTeradata Vantageの統合
  186. Intelligent Analytics for Telcos Using Teradata Vantage
  187. テラデータの差別化要因とその重要性
  188. 魅力的に輝くニューオブジェクトの誘惑と幻想
  189. Rising from the Ashes
  190. Today, I Join Teradata
  191. Using Data to Fight COVID-19 Supply Chain Disruption
  192. Legacy or Modern? Why not Both!
  193. 分析の価格設定モデル
  194. Using Advanced Analytics to Predict the Onset of a Cytokine Storm
  195. Connect Teradata Vantage with AWS Glue
  196. How to Balance Efficiency and Risk in Your Supply Chain
  197. How to Operationalize Enterprise Analytics in the Telco Industry
  198. How Companies Can Capitalize on Being Sustainable
  199. Navigating the Automotive Supply Chain Post-COVID-19
  200. The COVID-19 Pandemic and the Perfect Storm of Disruption
  201. Emulate Your Heroes with Data… and Vantage on AWS
  202. 中国での新型コロナ感染拡大時におけるデータ・アナリティクスの活用方法
  203. Introducing Teradata’s Incoming CEO Steve McMillan
  204. COVID-19: Risk Analytics for Building an Early Warning System
  205. What Is the Biggest Challenge Facing CMOs Today? Building, Measuring and Maintaining Brand Equity
  206. Automotive Industry: Navigating Post-COVID-19
  207. All Models Are Wrong (But Some Are Useful)
  208. How to Be Most Productive When Working from Home
  209. エンタープライズ規模の分析のコストの最小化
  210. It’s Your Data, Set it Free…
  211. COVID-19: Supply Chain and The Great Disruption
  212. Fighting Coronavirus with Teradata Vantage
  213. Breaking the COVID-19 Chain with Data Analytics
  214. How Teradata Vantage Brings Disruptive Innovation to Banking
  215. Connect Teradata Vantage to Azure Data Factory Using Custom Activity Feature
  216. Teradata and the MIT COVID Challenge Hackathon
  217. エグゼクティブが知っておくべきROIを生むアナリティクス ~皆さん、あなた方のアナリティクスのやり方は間違っています~
  218. My Grocery Shopping Experiences and ... Snowflake
  219. テラデータが中国でのCOVID-19蔓延防止対策をサポート
  220. How Bayes' Theorem Helps Prediction Analytics in Teradata Vantage
  221. People, We Need to Talk About Mass Electronic Surveillance
  222. Don’t let panic worsen the COVID-19 crisis: Let data run the supply chain
  223. Five Books Every CX Leader Should Read in this Time of Social Distancing
  224. Improving Prediction of the Unconfirmed COVID-19 Cases
  225. Teradata's Response to COVID-19
  226. Advanced Analytics for Coronavirus – Trends, Patterns, Predictions
  227. Reflecting on my Career in Data for Women's History Month
  228. 通信|Saudi Telecom Company (stc) の価値ある「答え」:
  229. An Introduction to Teradata’s R and Python Package Bundles for Vantage Table Operators
  230. How to Connect Teradata Vantage to Azure Blob Storage to Query JSON Files
  231. How to Repurpose Successful Database Techniques inside Teradata Vantage
  232. Teradata Has Been Named One of the World's Most Ethical Companies 2020
  233. What do you mean UX design is horizontal?
  234. Teradata is Launch Partner for New AWS Features
  235. Teradata Does Open Source! Introduction to the R and Python Packages for Vantage
  236. Why 2020 is the Year for 5G and IoT
  237. Norfolk Southern Corporation
  238. Data Privacy and Why it Matters to Our Customers
  239. Is Your Enterprise Being Disrupted by Consumerization?
  240. ハイブリッド・クラウドでのアナリティクス – アーキテクトの視点
  241. Not Just SQL Anymore! Using R and Python with Vantage
  242. 4 Trends that Will Revolutionize Data Management & Analytics
  243. Don’t Organize for AI, Organize for Analytics
  244. How Natural Language Processing Improves the Customer Experience
  245. Keeping a Lid on Concurrency within the Vantage Platform
  246. 6 Practices to Realize a Long-Term Data Vision Through Near-Term Work
  247. Teradata Experts on the Top Tech Predictions for 2020
  248. データアナリティクス:その本質はビジネスクエスチョンに対する「答え」を探ること
  249. Six Ways Teradata Vantage is Moving the Cloud Forward
  250. クラウドで実行するデータ・アナリティクス:単なる移行を越えて
  251. The Four Types of Chief Data Officers
  252. Customer Data Platforms: Silo Killer or Yet Another Silo?
  253. Is There a Geographic Component in Your Cloud Analytic Ecosystem?
  254. Vodafone Germany 5G
  255. What the Apple Card Controversy Says About our AI Future
  256. Rich Model, Poor Model
  257. Vodafone Germany Convergence
  258. Power to the People: Vantage Analyst in Action
  259. カスタマーエクスペリエンスを実現する、まったく異なる3つの戦略
  260. Forging Strategic Partnerships for our Customers
  261. Next-Gen Concepts for Player Performance and Wellness
  262. Embracing the Darkness: Vantage Developer
  263. テラデータ、クラウドを強化
  264. Survey: Success of Global Enterprise Depends on Adaptation to Hyper Disruption
  265. A Renewed Focus on User Experience at Teradata
  266. 8 Places to Visit in Denver While Attending Teradata Universe 2019
  267. Teradata Vantage and the Rhythms of Your Workloads
  268. The Future of Personalization: Deep Multi-Channel Hybrid Recommender System
  269. How to Deliver Better Business Outcomes with Predictive Modeling
  270. Teradata Certification Program Embraces Vantage
  271. ABANCA
  272. Time Series Analysis: Looking Back to See the Future
  273. Why Clean Data is Critical for Your Business
  274. Self-Service Analytics: Classifying Data and Analytic States
  275. Multitasking Within the Teradata Vantage Optimizer
  276. How Artificial Intelligence & Deep Learning Change the Game
  277. Vantage: A Cloud-First Integrated Data & Analytics Platform
  278. Taking Analytics to the 4th Dimension
  279. How Reinforcement Learning is Changing Customer Engagement
  280. Is Finance Holding Back Your Bank’s Digital Transformation?
  281. 3 Factors to Consider When Evaluating Self-Service Analytics
  282. Teradata Earns Spot (Again x2!) on Constellation ShortList for Hybrid Cloud
  283. Data is Not the New Oil. Data is Water!
  284. The Power of Prioritization in Data Management
  285. How Human Growth Defines the Future of Digital Disruption
  286. Cloud Analytic Migrations with Microsoft, Informatica & Teradata?
  287. Four Steps to Drive Digital Transformation in Your Bank
  288. Is Self-Service Analytics Sustainable?
  289. Why Multi-Dimensional Personalization is Worth the Investment
  290. Enterprise Data Strategy: The Upside of Scarce Funding
  291. What Should Your Enterprise Expect from its Cloud Analytics Vendor?
  292. Data Science for All: How to Bridge the Data Scientist Gap
  293. How to Enjoy Hybrid Partitioning with Teradata Columnar
  294. How Analytics Answer the Most Challenging Business Questions
  295. The Power of Integrated Data and Analytics
  296. 成功するアップグレードの5つのステップ
  297. Vantageが近年で最も人気のあるリリースである理由
  298. How Teradata and Oxford Saïd are Modernizing Analytics for Academic Research
  299. What Working “at Scale” Really Means
  300. Swedbank Delivers Superior Customer Experience by Illuminating the Customer Journey
  301. クラウドへの移行が理想的なユーザーエクスペリエンスの構築に役立ったTicketmaster
  302. AI for Industrials: Why is it different?
  303. テラデータの最新分析ソフトウェアにアップグレードするべき4つの理由
  304. The Data Lake is Dead; Long Live the Data Lake!
  305. What Tableau Customers Should Expect Post-Salesforce Acquisition
  306. 新しいAs-a-serviceモデルのVantageによる簡素化とモダナイゼーション
  307. Why Hadoop Failed and Where We Go from Here
  308. 3 Easy Ways to Turn Data into Actionable Answers
  309. How to Drive Marketing Personalization in an Increasingly Non-Personal World
  310. How Air France-KLM Group Uses Cross-Channel Analytics to Smoothly Connect Over 100M Passengers
  311. How Does Compounding Interest Relate to Your Investments in Data & Analytics?
  312. 5 Myths You Have Been Told About Industrial AI
  313. What Is the BYNET and Why Is It Important to Vantage?
  314. Why is a Real Time Interaction Manager (RTIM) Essential to Providing a Superior Customer Experience?
  315. 3 Ways New As-a-Service Offerings Bring Choice and Flexibility to Teradata Vantage
  316. How to Use AI and Video Analytics to Give Your Retail Business a Competitive Edge
  317. How U.S. Bank Uses A.I. and Machine Learning to Deeply Personalize Your Banking Experience
  318. How to Analyze Data at Speed and Scale Using Pervasive Data Intelligence
  319. Why Smart Cities Need Intelligent Data
  320. The Eight Functions You Should Consider When Choosing a Self-Service Analytics Platform
  321. Why You Get Faster Query Results with Teradata’s Adaptive Optimizer
  322. 6 Lessons for Women in Tech
  323. Teradata Has Been Named One of the World's Most Ethical Companies 2019
  324. What Is Pervasive Data Intelligence?
  325. How to Use Analytics to Avoid Business Problems
  326. Adding Cloud to Your Analytic Ecosystem
  327. Building a Diverse and Inclusive Teradata
  328. Is Your Data Scientist Team Contributing to Your Company’s ROI?
  329. Managing Analytic Workloads with Cloud
  330. Cash Is Still King – Make Sure Your Business Is Prepared for the Next Recession
  331. It's the Relationship - Not Just the Data - That is Critical to Success
  332. The Utah Jazz Uses Pervasive Data Intelligence for Next Generation Sports Analytics
  333. What Lessons Can Apollo 13 Teach Us About Analytics?
  334. Is There Such a Thing as Too Much Parallelism?
  335. The First Mistake of a CDO: Proposing Business Value
  336. Simpler Is Better. Until It Isn’t.
  337. How to Fill Your AI Talent Gap
  338. Five Challenges to Building Models with Relational Data
  339. How Painful is it (Really) to Switch Cloud Providers?
  340. Using Data to Answer the Key Challenge to Enterprise Reinforcement Learning
  341. What Happened to Big Data?
  342. Enterprise Opportunities to Apply Reinforcement Learning & AI
  343. Who Was Smarter, Karl Benz or Sigmund Freud?
  344. The Circle and Square, All You Need to Know About Data and Analytics
  345. How Data Privacy Can Be Good for Your Business
  346. Ensuring Actionable Answers from Analytic Models
  347. Cloud Nine: All Your Analytics, Wherever You Want Them. Really!
  348. Making Your Time-Based Analytics Fly Faster
  349. Moving from Mapping Customer Journeys to Guiding Them
  350. A Day in the Life of a Data Scientist with Teradata Vantage
  351. Real-Time Analytics or Real-Time Decision Making?
  352. What's Next in Tech: Teradata's Experts Weigh in on 2019 Predictions
  353. Artificial Intelligence and Machine Learning: Lessons and Opportunities
  354. New! Teradata IntelliCloud for AWS Marketplace (with Metered Billing)
  355. Enabling Trusted Data within a Teradata Analytical Ecosystem
  356. Reimagining Analytics and Herding Unicorns
  357. Connecting the Dots: Accelerating Analytics into Answers
  358. Governing Data Across the Analytical Ecosystem
  359. Unleash Human Expertise with Pervasive Data Intelligence
  360. Make Data Intelligence Pervasive
  361. Customer "Jobs to be Done"
  362. North Star or Shooting Stars for Sustainable Analytics at Scale?
  363. A Special Message of Appreciation
  364. Teradata's Autonomous Platform - Automation Made Intelligent
  365. The Road Ahead: Integrating Amazon S3 and Azure Blob into Teradata Vantage
  366. Analytic Insights Remain Trapped in Complexity and Bottlenecks
  367. Stages of Grief for Data Scientists and It Alike: Making Open Source Work in Paranoid Corporations, Part II
  368. Teradata Vantage - Doing For Analytics What We Did For Data
  369. Teradata: Stop Buying Analytics. Start Investing in Answers.
  370. Increase Productivity: Rev Up Your Teradata System
  371. What Is the Teradata Analytics Platform and Why Is This Big News for an Analytics Professional?
  372. 36 Cloud Sessions at Teradata Analytics Universe
  373. Stages of Grief for Data Scientists and It Alike: Making Open Source Work in Paranoid Corporations
  374. What if Data Was an Asset?
  375. A View From the Trenches: What Should an Analytics Professional Evaluate When Purchasing an Analytics Solution?
  376. IT’s Identity Crisis
  377. Which Analytic Workloads Should Move to the Cloud First?
  378. Intellectual Curiosity—The Fuel that Drives Effective Analytics
  379. Teradata Passes GDPR Audit for Cloud Service
  380. Creating the Critical Conditions for Cloud Analytics to Thrive
  381. Teradata Earns Spot (Again!) on Constellation ShortList for Hybrid Cloud
  382. Controlling the Supply Chain: How digitalization and analytics will dramatically change your world!
  383. Redefining Modern Data Architecture
  384. How Burnout, Culture and Safety Analytics Contribute to Employee Wellness Programs
  385. Have Billions of Dollars in Organizations, Technology and Regulatory Fines Actually Reduced Money Laundering?
  386. Running Millions of Queries Per Day in the Cloud
  387. Putting AI to Work in the Finance Industry
  388. Finding the Signal in the Customer Experience (Cx) Haystack
  389. Social Psychology Analytics of Employee Stress – Through the Lens of Clinician Burnout
  390. Marketing to Machines in the Age of Algorithms: Part II
  391. Is Data Really an Asset?
  392. Engineering Customer Experience: Customer Centric Feedback Loops
  393. Microsoft Azure Update: Teradata in the Cloud
  394. Amazon Web Services (AWS) Update: Teradata in the Cloud
  395. The Fastest Path to The Cloud Starts with Knowledge: Start Small, Scale Fast
  396. The Real Hurdle to Succeeding with Analytics
  397. Taking Compliance Seriously
  398. Good Investment: Why Banks Need to Open up to the Cloud
  399. How is Analytics Helping Banks to Keep Pace with Regulatory Demands?
  400. The Future of Marketing Key Takeaways
  401. Considerations When Thinking About Moving Your Analytical Ecosystem to the Cloud
  402. Path to the Cloud: Know Your Deployment Options
  403. Data Analytics: A Prerequisite to Artificial Intelligence Mobility
  404. How to Crawl, Walk and Run with AI
  405. When the Time is Right to Try Cloud-Based Analytics
  406. 7 Citizen-Centric Sectors That Can Be Enhanced by Artificial Intelligence
  407. The Next Digital Revolution: The Amazing/Terrifying Future of Financial Services
  408. Scalability in the Cloud: Why it Matters
  409. The Best Way to Predict Your Future: Analytics for Tomorrow’s World
  410. Don’t Compromise on Customer Experience
  411. Outsourcing for Governments: Analytics can help to make the right choice (part 3)
  412. How Cloud Based Analytics Play a Role in Determining Tomorrow’s Winners
  413. Be Different
  414. Is crossing the Smart City by Air Taxi so farfetched?
  415. Show Me the Money: Subscribe to and Pay Only for What You Use
  416. Snowflake’s Credibility Melting Fast
  417. Outsourcing for Governments: Analytics can help to make the right choice (part 2)
  418. Engineering the Customer Experience
  419. The State of Analytics in the Cloud
  420. Outsourcing for Governments: Analytics can help to make the right choice (part 1)
  421. Self-service vs. As-a-service – Which Is Better?
  422. Sasol: Using Analytics and Data in the Cloud to Create and Deliver Cost Efficient Energy Around the World
  423. The Surprising State of Analytics in the Cloud
  424. Teradata Opti Awards Call for Entries
  425. The Least Risky Decision You’ll Ever Make
  426. How Much Is IoT-Driven Industry Convergence Going To Cost Your Business?
  427. Grass for the Cows and Power to the People: Why GDPR and Digital Progress are Not Contradictory
  428. What today’s machine learning and AI is and is not
  429. A Trusted Adviser: The Role of Consultants in Cloud-based Analytics
  430. The Future of Banking
  431. Why Organizations Struggle with Customer Experience!
  432. Too Much Information? Why ROI Should Really Mean Return on Information.
  433. The Chief Data Officer’s To-Do List
  434. Security in the Cloud—A Little Known Advantage, Actually
  435. Your data needs you – why driving change is the key to successful analytics
  436. Snowflake Claims 100,000% Cost Savings vs. Teradata – You Can’t Make This Stuff Up!
  437. The Evolution of Teradata – The Passion of our Past is the Fuel for our Future
  438. "Retire Teradata" - Dream On, Snowflake
  439. Leading the Way to Enterprise Analytics in the Cloud
  440. Digital Supply Chain – Fact or Fiction?
  441. "Built for the Cloud" vs "Built for Analytics" - You can have both with database scalability
  442. Is Good Enough Really Good Enough?
  443. Could big data analytics and deep learning have detected India’s largest banking fraud?
  444. Leveraging artificial intelligence in the fight against global wildlife poaching
  445. GDPR - The Final Countdown…and Beyond
  446. Why AnalyticOps Empowers Automation and AI
  447. Transforming the transformers: Demystifying data for power network transformation
  448. Guided Analytics: An Example With Path Analysis
  449. BIDMIO - The Path to Analytic Insight
  450. It's a small world after all
  451. Driving Data Science Results By Asking Why
  452. Curiosity never killed the analytical cat
  453. Gotcha! New Visualization Techniques Make Fraud A Whole Lot Easier To “See” — And Stop
  454. Standard Chartered: Creating a Golden Source of Financial Data to Continue Being, “Here for Good”
  455. What is the difference between automated and autonomous decisions?
  456. Five focus areas for success in advanced analytics
  457. What are the prerequisites for a large-scale AI initiative?
  458. Machine learning for Telcos 5G: a network of networks
  459. Don't let analytics bureaucracy dictate your pace
  460. Analytics at Scale: What Data Analysts Need to Know
  461. ポジティブなビジネス成果のためのデータと分析の5つの大きな利点
  462. Spend more time on analytics and less on data prep
  463. What is the definition of AI?
  464. How IoT won the war
  465. Getting from A to B – How Customer Journey Is Changing the Customer Experience
  466. The new age of customer trust
  467. AI without machine learning
  468. Defining a Successful AI Strategy for 2018: Key Thoughts from a Data Scientist
  469. Not All Machine Learning Leads to Artificial Intelligence
  470. 8 tips to prove ROI when deploying analytics in the industrial sector
  471. What is machine learning?
  472. A value-driven approach to telco customers, possible through advanced analytics
  473. Big Data - The Big Missed Opportunity
  474. Wait, maching learning and artificial intelligence aren't the same?
  475. Teradata IntelliCloud Now Available on Microsoft Azure
  476. Internet of Things for Insurance - The Future is Now
  477. European bank goes from 0 to 60 in analytics endeavor
  478. Is the Lack of an Analytics Culture Holding Your Company Back? There’s Help.
  479. Why Enterprise AI Will Be Highly Differentiating
  480. Unsilo your workforce to unite your data
  481. When Marketing Meets Finance
  482. Avoiding Common Mistakes with AI
  483. Creativity and Critical Thinking in the Age of Enterprise AI
  484. Can Big Data Help Control India’s Spiraling Pollution?
  485. How a Telco Values Customer Loyalty Using Teradata and Advanced Analytics
  486. Uncovering Analytic Opportunities
  487. Three Implications of AI for the Enterprise
  488. Customer Journey Management and Analytics: Chicken and Egg
  489. Teradata is on a Mission! And, 2017 was a Big Step Forward
  490. Is it Too Late for Your Business to Win the Race to AI?
  491. Smart Cities 2.0 - Boosting Citizen Engagement
  492. The Future of AI for Enterprises: A Q&A with Sri Raghavan:
  493. BYOL, Fold/Unfold Now Available on Both Azure, AWS
  494. From Senegal to North Korea: Finding New Analytics Solutions to Fight Economic Disparity
  495. Understanding Teradata Elasticity
  496. Built like Blockchain? Creating a Foundation for Trusting AI Models
  497. The Culture of Value Measurement
  498. Q&A with Sri Raghavan: Applying Advanced Analytics to Health Care
  499. It all Started with ‘CARE’ – Reasons to Pay it Forward
  500. Can We Trust Hadoop Benchmarks?
  501. ETL is changing: How to transform a TLA*
  502. Taking customer journey from mapping to guiding
  503. Four tips to delight your CFO and unlock the value of data assets
  504. Behavior and Culture: The Next Steps Toward 'The Sentient Enterprise'
  505. Hype versus hope: Upcoming applications of AI
  506. Cryptocurrency skepticism: Is blockchain the Netscape of 2017?
  507. Building Deep Learning Machines: The Hardware Wars Defining the Future of AI
  508. Behavioral segmentation through path analysis
  509. Is Unstructured Data a “Trick or Treat” for your Organization?
  510. Don’t Rely on Witchcraft: Question the Status Quo of Customer Analytics
  511. Lessons from the Sentient Enterprise: To Scale Your Analytics, “Merchandise” the Insights
  512. Making the Most of Your Time
  513. More Cloud Milestones for Teradata: Azure, AWS, IntelliCloud
  514. Teradata IntelliSphere — a unified software portfolio for a unified analytical ecosystem
  515. Simplicity out of Complexity: Announcing the Teradata Analytics Platform
  516. Advanced analytics for a new era
  517. Just imagine: Analytics expertise on demand from Teradata
  518. Fast Track Business Outcomes from Artificial Intelligence with Proven Methods and Accelerators
  519. Retail: How to drive growth with advanced analytics
  520. What does real-time analytics for customer experience really mean?
  521. Mixing Operational and Customer Data for Aviation Business Insights
  522. The Sentient Enterprise. Why Another Book on Analytics?
  523. Can Big Data Help Reduce India’s Burden of Healthcare Costs?
  524. The New Wave of Machine Learning
  525. Survey: State of Artificial Intelligence for Enterprises
  526. The Tree of Machine Learning Algorithms
  527. Is that a bully in your sentence?
  528. Artificial Intelligence Unstuck: How Competition, Not Bureaucracy, is Moving AI Forward
  529. Lessons from the Sentient Enterprise: Three Big Predictions from the Pros
  530. The Age of Automation: Where does creativity fit in?
  531. That (Amster)damn utilities data…
  532. Open Source AI is in the Same Place Big Data Was 10 Years Ago
  533. Is failure good for your data scientists?
  534. Teradata Database 16.10 Now on Azure and AWS Marketplaces
  535. Within data and analytics, the “If you build it, they will come” mentality is finally dead
  536. The 9 steps every business analyst should take
  537. Who owns the customer experience in the digital age?
  538. Could the English Language Get Any More Confusing?
  539. The Uberization of Analytics
  540. Occam’s Razor and Machine Learning
  541. Hybrid Cloud Use Cases
  542. Objectives and accuracy in machine learning
  543. Are there relics in your data management?
  544. Going to the cloud? Benefit from the amazing experiences of those who are having success at PARTNERS 2017
  545. What It Means To Partner With A World-Class Sales Organization: Part Three
  546. Is analytics operations the key to successful data science?
  547. Five ways Analytics and Data Science can add business value
  548. The secret to AI in the Enterprise could be little-known transfer learning
  549. What It Means To Partner With A World-Class Sales Organization: Part Two
  550. A message from Teradata CEO, Victor Lund
  551. It’s time to wake up to the big data gold mine
  552. Henry Ford Didn’t Build a Faster Horse – and Neither Should You
  553. ‘Game’ theory: Perfecting in-app purchasing through analytics
  554. Blockchain in your supply chain: What’s all the hype about?
  555. What It Means To Partner With A World-Class Sales Organization
  556. TD Team Spotlight: Koontz draws strength from lifting up others
  557. Lessons from the Sentient Enterprise: Business data meets business culture
  558. Data and analytics in financial services — a challenge or an opportunity?
  559. Have CFOs Changed Their Mindset When It Comes to Data?
  560. The future of marketing: Q&A with Andrew Stephen and Yasmeen Ahmad
  561. Getting value from attribution analytics, according to Gartner
  562. Myth Versus Reality: The Truth About Cloud Security
  563. What today’s machine learning and AI is and is not
  564. Security: It’s not just about keeping the bad guys out
  565. Deep learning for executives: The killer apps for deep learning
  566. Part Two: Age of the Machines – Predicting the Human and Machine Partnership
  567. Your data needs you – Why driving change is the key to successful analytics
  568. Teradata Bolsters Analytics and Database Capabilities for Microsoft Azure
  569. Bean Counter Or Business-Growth Enabler? What Can The CIO Learn From The CFO?
  570. The future of marketing — it’s (still) the data, stupid
  571. Big data and the fight against human trafficking
  572. Danske Bank: Innovating in Artificial Intelligence and Deep Learning to Detect Sophisticated Fraud
  573. How Curiosity Saves Your Company … And Turns Your People Into Citizen Data Scientists
  574. GDPR in 3 Easy Steps
  575. Deep Learning for Executives: How Will it Change Your Business?
  576. The future of marketing – You don’t own your brand anymore
  577. IntelliCloud Now in AWS Ireland – and Much More!
  578. Introducing the Path Analysis Interface for Teradata
  579. Unchartered Waters: Machine Learning in Geoscience
  580. The future of marketing — is it really all about #data?
  581. Analytics, data science, ethics, robots and GDPR at ‘The Future of Marketing’ event
  582. Maybe you can’t machine learn everything – but does that mean you shouldn’t try?
  583. Big Data and the Fight Against Climate Change
  584. Who Wins with Cloud Adoption?
  585. Teradata Cares for the Munich Orphanage
  586. Breaking Up the Boys’ Club to Unlock the Tech Industry’s Untapped Potential
  587. Deep Learning for Executives: What Exactly is it Again?
  588. Deep Learning: New Kid on the Supervised Machine Learning Block
  589. Why The CFO Cannot See The Value Of Data And Analytics In The Balance Sheet
  590. Open Banking – For Whom?
  591. Big Data Brings Recruitment into the 21st Century
  592. Building the Machine Learning Infrastructure
  593. The Outcome Economy, Powered by IoT
  594. Working in the New World of Data and Analytics
  595. Team Effort Makes a Big Difference in the Community
  596. Team Effort Makes a Big Difference in the Community
  597. Doing Our Part to Close the Skills Gap
  598. The Promise of Artificial Intelligence: Where We’re Headed and Whence We’ve Come
  599. The Future of Marketing: Bringing Together Business and Education to Close the Skills Gap
  600. Sanofi: Forwarding Medical Advances and Breakthroughs to Help People Have Better Health
  601. The Complex Role of Data in Today’s Digital Revolution
  602. Neil Armstrong and DHL—Two Giant Leaps for Mankind in a Single Year
  603. PNEC#21 and a Unique Take on the Value of Analytics
  604. Data Science Versus Data Engineering
  605. Defining the CDO: Gatekeeper vs Innovator
  606. Lufthansa Group: Connecting Europe to the World While Keeping the Customer at the Center of Business
  607. Should Data Modelling be a ‘Prescriptatorship’, or Take a More Laissez-Faire Approach?
  608. Why “Unsupervised,” Autonomous Cars are Right Around the Corner
  609. Mind the Gap: Cloud as a Temporary Fix
  610. Predicting the Path of Predictive Analytics
  611. The Future of Health and Human Services Data Modeling (Part 2)
  612. Stuck in a Marketing Rut? Key Questions to Ask Yourself
  613. Improve your marketing through AI-influenced analytics
  614. Discovery, Truth and Utility: Defining ‘Data Science’
  615. The Future of Health and Human Services Data Modeling (Part 1)
  616. Machine Networks – Competitive Strength In Numbers
  617. Spaghetti Bolognese: A Recipe for Creating More Effective Promotions
  618. Machine Learning Goes Back to the Future
  619. How Are Customers Like Bees? They Rarely Travel a Straight Path or Make a Single Stop
  620. The Business Impact of Machine Learning
  621. Optimize the End-to-End Customer Experience with Business Analytics Solutions
  622. Understand the Customer Through Art
  623. AI is Red Hot. But Where Is All This Innovation Pointing Us
  624. Customer Journey Analytics – One Bite At A Time
  625. Proprietary Analytic Approach Accelerates Time to Value
  626. No, You Can’t Machine Learn Everything
  627. Standing With Women in Tech: Tips for Success
  628. Five Ways Cloud Vendors Are Dealing With Data Privacy Concerns
  629. The Age of the Machine
  630. Teradata on Azure: Available Now!
  631. Path Analytics Shouldn’t Be This Difficult!
  632. Unprecedented Power & Performance Upgrades for Teradata IntelliFlex®
  633. Teradata Jumps Ahead: Flexible Licensing Choices Change Everything
  634. Synchronicity: Teradata’s Two Key Q1 Cloud Milestones
  635. The New Data Analytics Use Cases: Hybrid Cloud Takes Center Stage
  636. Five Key Findings from the Teradata Global Data and Analytics Trends Study 2017
  637. Disruption and Leadership on Gartner’s DMSA Magic Quadrant
  638. Introducing Teradata IntelliCloud: Our Next Generation Managed Cloud
  639. Analyzing the Analytics
  640. Business Reasons for Analytics
  641. IoT - Just What the Doctor Ordered!
  642. Teradata Strengthens Hybrid Cloud Commitment with Teradata Database on Azure
  643. Ditch the Old Ways of Product Management. Say Hello to Product Innovation.
  644. Expect the Unexpected: Real Stories of Challenges that Slow Digital Transformation
  645. Disrupt Thyself: A 3-Point Plan For Innovation At Large Enterprises
  646. The Analytics and Leadership Mandate for Digital Transformation
  647. Three Reasons Our Customers Are Excited About Teradata Everywhere™
  648. Borderless Analytics: Taking Complexity Out of Today’s Analytical Ecosystem
  649. Teradata Aster makes it Easy to Unlock New Insights from Hadoop Data
  650. Digital Transformation: Are You Winning Battles, Yet Losing the War?
  651. Part Two: How to Make the Value of Data and Analytics Visible to the CFO
  652. Analyzing your Analytics
  653. Hacking IoT: Fast-Tracking Transformational IoT Solutions
  654. Data-Driven Insights Are All Around Us – Are You Listening?
  655. Is Your Business Agile? These Three Ways Can Help You Find The Answer
  656. Three Ways to Run Your Global Business With Startup Agility
  657. Is Your Data Lying to You?
  658. The Future Of Hadoop Is Cloudy, With A Chance Of Growing Ecosystem
  659. The Secret to Big Data Analytics Success Comes Down to One Word
  660. Struggling to Get Faster Data-Driven Insights? Take this Lesson from the Telecom Industry
  661. Will Data Anarchy Shut Down the Big Data Revolution?
  662. A LinkedIn For Analytics: Helping Analytic Insights Go Viral In Your Business
  663. The Ergonomics of Human-Data Interaction
  664. Is Your Enterprise ‘Sentient?’ Building A Smarter, More Agile Business

Turn your complex data and analytics into answers with Teradata Vantage.

Contact us