The Future of Analytics or The New SQL

Transcription

1 The Future of Analytics or The New SQL Gerhard Otterbach, Sales Manager Teradata Germany Hanau, Feb. 28th, 2018

2 Teradata At A Glance: 39 Years Ago Teradata was big data before there was big data Donald Feinberg, Gartner

3 Teradata At A Glance Technology Solutions Our Portfolio: Scalable and highperformance DBMS, Analytic and Integration Fabric technologies, available on-premise and in the Cloud Teradata database, Teradata Aster Analytics, Hadoop Teradata QueryGrid, Presto, Listener, Unity, AppCenter > Highimpact business outcomes Business Solutions Solving business problems through innovative use of data and analytics: Data and Analytic Strategy Business Value Frameworks Data Science Services Architecture Expertise Design, build, deployment, maintenance and operation of Analytic solutions based on Teradata and Open Source technologies: Data Strategy and Roadmaps Ecosystem Architecture Design and Implementation Managed Services ~1,400 + Customers in 77 Countries ~10,000 Employees including ~5,000 Consultants Market Cap: U.S. $4 Billion+ World s Most Ethical Companies Ethisphere Institute Fortune: Top 10 U.S. Software Company The Completeness of Vision leader in Gartner s Magic Quadrant Data Warehouse and Data Management Solutions for Analytics Leader in the Forrester Wave : Big Data Hadoop-Optimized Systems In-Memory Database Platforms

4 4 Challenge I The Big Data Landscape

5 Challenge II The Never Ending Fight But who is right? SQL vs. No-SQL 5

6 Challenge II The Never Ending Fight But who is right? SQL AND! No-SQL 6

7 Challenge III Data Lake? Governance/Control vs. No Control 7

8 Challenge III Data Reservoir! Controlled No Control 8

9 Challenge IV Artificial Intelligence Hype Analytical Evolution in the past 30 years Prescriptive Predictive Descriptive REPORTING What is happening? 1990s ANALYZING Is it real? Why is it happening? PREDICTING What are the hidden patterns? What will happen next? OPERATIONALIZING What is happening right now? 2000s ACTIVATING Make it happen with automation. MACHINE LEARNING Self-learning systems with regression. 2010s DEEP LEARNING Deep neural networks. 9

10 Challenge IV Artificial Intelligence Hype Artificial Intelligence outside the Charts Hard touch down to be expected! Artificial Intelligence Deep Learning Machine Learning Data Science Predictive Analytics Big Data Advanced Analytics Data Mining IDA Source: Alexander Linden, Gartner BI Summit, March

11 The solution: Analyze Anything Tools and Languages Connectors and APIs SQL/No-SQL Engine Adv. Analytics Engines Data Mgmt. Engine AI Engine Custom Engines Analytic Functions, Engines, and Data Types 11

12 The solution: The Teradata Analytics Platform Tools and Languages Connectors and APIs Teradata + Hadoop TD ASTER SPARK TensorFlow Custom Engines* 12 * Future Analytic Functions, Engines, and Data Types Storage: Teradata, Hadoop, S3/BloBStorage Deployment Options: On Premise; Public Cloud, Private Cloud; Hybrid

13 The solution: The Teradata Analytics Platform Languages SQL, Python, R, C/C++, JavaScript, Java, Perl, Ruby Tools Jupyter, RStudio, KNIME, SAS, Dataiku Teradata Engine Cross Engine Orchestration Aster Engines Spark Engine Tensor- Flow Engine Custom Engine* Hadoop S3/BloB* SQL Access QueryPoint, BI and Visualization tools Persistent Storage S3/BLOB Storage* Others 13 * Future

14 Teradata Analytics Platform Deployment Strategies Analyze Anything Deploy Anywhere Buy Any Way Move Anytime Teradata Cloud Public Cloud Teradata Hardware Commodity Hardware Same Teradata Software across all deployment options enables seamless application portability 14

15 To Summarize Analytics Landscape is and will remain complex SQL and No-SQL will remain next to and combined with each other Artificial Intelligence is not a hype but operationalization is a must An everywhere Analytics Platform that integrates newest tools, engines, languages and storage systems is the key to success! 15

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