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Mythbusters NOSに関するお知らせ。
クラウド

Native Object Store (NOS)で始めよう

クラウド・オブジェクト・ストアを検討されているなら、Teradata Vantage 2.0 aaSを使用してAWS-S3とAzure Blobのオブジェクト・ストアにオンデマンドで簡単にアクセスしましょう。

7月 6, 2020 | 1 分で読める
編集者のお薦め
データ分析に関する独立したアナリスト評価で、テラデータが最高スコアと1位の座を獲得
ビジネスアナリティクス

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

Vantage on AWS
クラウド

AWSファーストパーティ・サービスとTeradata Vantageの統合

Vantage on Microsoft Azure
クラウド

Microsoft Azureファーストパーティ・サービスとTeradata Vantageの統合

テラデータは、先進的なデータウェアハウスです。
Vantage

モダナイゼーションに必要なのは、シンプルさと高度さ

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

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