Oracle Big Data, Machine Learning, DW OOW újdonságok

Transcription

1 Oracle Big Data, Machine Learning, DW OOW újdonságok Fekete Zoltán Platform principal presales consultant

2 Safe Harbor Statement The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, timing and price of any features or functionality described for Oracle's products may change and remains at the sole discretion of Oracle Corporation. Statements in this presentation relating to Oracle s future plans, expectations, beliefs, intentions and prospects are "forward-looking statements" and are subject to material risks and uncertainties. A detailed discussion of these factors and other risks that affect our business is contained in our SEC filings, including our most recent reports on Form 10-K and Form 10-Q, particularly under the heading "Risk Factors." Copies of these filings are available online from the SEC or by contacting Oracle Corporation s Investor Relations Department at (650) or by clicking on SEC Filings on Oracle s Investor Relations website at All information set forth in this presentation is current as of October 3rd, Oracle undertakes no duty to update any statement in light of new information or future events. 2

3 Október 1-5.

4 OOW előadások letöltése OOW előadások HA, MAA, Exadata Expected CY

5 Database Cloud szolgáltatások mindenkinek 100% kompatibilis, belépő szinttől a működéskritikus rendszerekig Express Database Exadata Adatbázis fejlesztés KKV és osztály szintű alkalmazások Enterprise alkalmazások MAA, skálázhatóság és teljesítmény Platform jellege Megosztott Dedikált Engineered

6 Database Cloud szolgáltatások mindenkinek All packages: Oracle Database Transparent Data Encryption. Standard package: Oracle Database SE2. Enterprise package: Oracle Database Enterprise Edition, Data Masking and Subsetting Pack, Diagnostics and Tuning Packs, Real Application Testing. High Performance: Multitenant, Partitioning, Advanced Compression, Advanced Security, Label Security, Database Vault, OLAP, Advanced Analytics, Spatial & Graph, Database Lifecycle Management Pack and Cloud Management Pack for Oracle Database. Extreme Performance: RAC (Real Application Clusters), Active Data Guard, Database In-Memory

7 ma

8 Oracle Autonomous Data Warehouse Cloud 8

9 Introducing: Autonomous Data Warehouse Cloud Easy Automated management Automated tuning: Simply load data and run Fast Based on Exadata technology Elastic Instant scaling of compute or storage with no downtime Expected CY

10 Oracle Autonomous Database World s First Autonomous Mission Critical Database Self-Driving, Self-Securing, Self-Repairing Full End-to-End Automation Autonomou s Database Less Labor, Lower Cost, Fewer Errors, More Secure, More Reliable Frees DBAs from generic operational drudgery to innovate more Runs World s #1 Database, Specialized by Workload In Public Cloud or Cloud at Customer 10

11 AI Platform Cloud Service 11

12 Introducing: AI Platform Cloud Service (coming soon) Easy Setup Complete ML dev. env., tools, GPU drivers Pre-integrated models and tools Easy Access to Data Sources: BDCS, DBCS, MySQLCS, EHCS, Fast Infrastructure: GPUs, flash storage, 25 Gb. Highly performant Accelerate App Development ML models exported, to use in applications, which can be developed quickly with the rich set of services and tools available in Oracle PaaS. 12

13 Information Management Reference Architecture Input Events Actionable Events Actionable Data Sets Actionable Metrics Streaming Engine Data Lake Enterprise Data & Reporting Structured Enterprise Data Execution Innovation Data Discovery Lab Discovery Output 13

14 Big Data Appliance X7-2 Sun Oracle X7-2L Servers with per server: 2 * 24 Core (2.1GHz) Intel Xeon Platinum 8160 ( Skylake ) Processors 256 GB DDR Memory, expandable to 1.5TB 12 * 10TB, 7,200 RPM Disks for a total of 120TB storage 40Gb/sec InfiniBand Internal Network, 10Gb Ethernet External Included Software (4.10): Oracle Linux 6.x & Oracle Linux 7.x for Edge Nodes Oracle Big Data SQL* Cloudera Distribution of Apache Hadoop EDH Edition Cloudera Manager Oracle R Distribution Oracle NoSQL Database CE * Oracle Big Data SQL is separately licensed 14

15 Vision for Oracle Big Data Cloud: The Ideal Big Data Platform Elasticity - We believe the architecture of the future uses leading-edge servers for compute and storage, from 3 nodes Deep Engineering - We believe engineering hardware and software together enables transformational Big Data, Analytics and Machine Learning in a single platform Cloud without Compromise - We believe the Cloud of the future combines the advantages of Deep Engineering with the agility and cost of Cloud, and 100% on-premises compatibility 15

16 Implementation: Oracle Cloud Services Oracle Analytics Cloud Service Oracle Big Data SQL Cloud Service Oracle Big Data Cloud Service Big Data Manager R & ORAAH Spatial & Graph Kafka Cloudera CDH Enterprise Data Hub Oracle Database Cloud Service Connectors Oracle Storage Cloud Service 16

17 Focus: Oracle Big Data Cloud Service Oracle Big Data Cloud Service Big Data Manager ODCP Kafka Zeppelin Cloudera CDH Spark R & ORAAH Big Data Cloud Service Hive Spatial & Graph Connectors Big Data Cloud Service at Customer 17

18 Credits or Subscription Secure Setup (default = Y) Node Configurations Associate Storage Cloud Service 18

19 What did you just do? Allocated a set of nodes from the pool Configured the IB network to ensure secure tenancy Created VMs to host the Hadoop cluster Enabled 32 OCPUs Delivery 48TB of Disk And 256GB of memory Created a CDH cluster in a standard and certified manner Created the HDFS file system, configured Yarn, Spark Enabled HA for CDH components like NameNodes, Zookeeper, etc. Configured the client network for client access Applied latest Best Practices for Cloudera Set up Set up the edge nodes if selected in cluster creation Enabled Kerberos on the cluster for all services and integrated with IDCS* Connected to Storage Cloud to enable ODCP for data copy back and forth Set up MySQL in Active-Passive mode for Hive metastore Configured Big Data Manager Configured Key Trustee Server in HA mode for HDFS encryption Configured R and ORAAH* Set up Sentry for SQL access security Enabled Hue, Cloudera Manager Zeppelin Notebooks and Interpreters And a bunch of stuff we casually forgot about 19

20 20

21 Machine Learning Computers Learn from Patterns in the Data and Make Predictions Machine learning relies on large amounts of accurate training data More volume of accurate data increases learning Increased learning/training means more accurate predictions Anomaly Detection: Separate normal from abnormal patterns in the data Detect a cancer cell from a normal cells Detect the CFO logging on from a computer in the Ukraine 21

22 Complete and Integrated Management and Security Cloud One suite, one vendor, one cloud Unified data architecture Secure & manage any technology On-premise, Oracle Cloud, AWS No integration required High degree of automation Configura tion Logs SIEM + Applicatio UEBA n to Infrastruc ture Monitori ng Remediat ion Analytics ML based anomaly detection Easy to operate and use Integrates with Enterprise Manager 22

23 World s First Cloud Native Management & Security System Complete and Integrated System Monitor and analyze ALL users and assets in a single system Powered by Machine Learning (ML) ML-based insights and anomaly detection Configura tion Logs SIEM + Applicatio UEBA n& Infrastruc ture Monitori ng Remediat ion Analytics Automated Remediation Automated operational workflows and real-time security remediation 23

24 Move Data Between Apache Hadoop and Oracle Database Fast data movement Support multiple data formats: Parquet, ORC, text, Oracle Data Pump Map types between source and target Simple, intuitive CLI and SQL Developer UI Works with Big Data and Database Cloud Services Load into Database Oracle Loader for Hadoop Parquet, ORC Text, Oracle Data Pump Convert into Oracle internal format and load Copy to Hadoop 24

25 Simple, Intuitive CLI Load into Oracle Database load oracle table jdbc0:movie_ratigns from hive table hive_moviedemo:traffic_lights using directpath Copy from Oracle Database create or replace hive table hive_moviedemo:movie_ratings_db from oracle table jdbc0:movie_ratings Load into Database Oracle Loader for Hadoop Parquet, ORC Text, Oracle Data Pump Convert into Oracle internal format and load Copy to Hadoop 25

26 SQL Developer Example GUI: Copy to Hadoop 26

27 Traditional vs. Oracle Machine Learning/Predictive Analtyics Traditional Move the data Move the algorithms Simpler, Smarter Data Management + Analytics / Machine Learning Architecture

28 Oracle s Machine Learning/Advanced Analytics Fastest Way to Deliver Scalable Enterprise-wide Predictive Analytics Key Features Parallel, scalable data mining algorithms and R integration In-Database + Hadoop Don t move the data Data analysts, data scientists & developers Drag and drop workflow, R and SQL APIs Extends data management into powerful advanced/predictive analytics platform Enables enterprise predictive analytics deployment + applications

29 Oracle s Machine Learning & Adv. Analytics Algorithms CLASSIFICATION Naïve Bayes Logistic Regression (GLM) Decision Tree Random Forest Neural Network Support Vector Machine CLUSTERING Hierarchical K-Means Hierarchical O-Cluster Expectation Maximization (EM) ANOMALY DETECTION One-Class SVM TIME SERIES REGRESSION Linear Model Generalized Linear Model Support Vector Machine (SVM) Stepwise Linear regression Neural Network LASSO ATTRIBUTE IMPORTANCE A1 A2 A3 A4 A5 A6 A7 Minimum Description Length Principal Comp Analysis (PCA) Unsupervised Pair-wise KL Div CUR decomposition for row & AI ASSOCIATION RULES A priori/ market basket Holt-Winters, Regular & Irregular, with and w/o trends & seasonal Single, Double Exp Smoothing PREDICTIVE QUERIES Predict, cluster, detect, features SQL ANALYTICS SQL Windows, SQL Patterns, SQL Aggregates FEATURE EXTRACTION Principal Comp Analysis (PCA) Non-negative Matrix Factorization Singular Value Decomposition (SVD) Explicit Semantic Analysis (ESA) TEXT MINING SUPPORT Algorithms support text type Tokenization and theme extraction Explicit Semantic Analysis (ESA) for document similarity STATISTICAL FUNCTIONS Basic statistics: min, max, median, stdev, t-test, F-test, Pearson s, Chi-Sq, ANOVA, etc. R PACKAGES CRAN R Algorithm Packages through Embedded R Execution Spark MLlib algorithm integration EXPORTABLE ML MODELS OAA (Oracle Data Mining + Oracle R Enterprise) and ORAAH combined OAA includes support for Partitioned Models, Transactional,Copyright Unstructured, Geo-spatial, Graph data. etc, 2017, Oracle and/or its affiliates. All rights reserved. C and Java code for deployment

30 1-Click, 100% Automated, SQL Predictive Queries Oracle s Machine Learning Accelerates New Possibilities Predictive Queries 1-Click immediate machine learning model build AND model apply as a SQL query 1-Click Predictions! Classification & regression Multi-target problems Clustering query Anomaly query Feature extraction query Automatically creates multiple anomaly detection models Grouped_By and scores by partition via powerful highly automated SQL query

31 Oracle s Machine Learning/Advanced Analytics Platforms Machine Learning Algorithms Embedded in the Data Management Platforms Analytics Producers Analytics Consumers Data Scientists, R Users, Citizen Data Scientists BI Analysts, Managers Functional Users (HCM, CRM) Data Management + Advanced Analytical Platform Big Data SQL Big Data Cloud Service Oracle Machine Learning Big Data Cloud ORAAH Machine Learning Algorithms, Statistical Functions + R Integration for Scalable, Parallel, Distributed Execution Database Cloud Oracle Machine Learning Database Edition Machine Learning Algorithms, Statistical Functions + R Integration for Scalable, Parallel, Distributed, in-db Execution

32 Oracle Machine Learning Machine Learning Notebook for Autonomous Data Warehouse Cloud Key Features Collaborative UI for data scientists Packaged with Autonomous Data Warehouse Cloud (V1) Easy access to shared notebooks, templates, permissions, scheduler, etc. SQL ML algorithms API (V1) Supports deployment of ML analytics

33 Confidential Oracle Internal/Restricted/Highly Restricted Introducing Data Integration Platform Cloud Overview Copyright Copyright 2017, 2017, Oracle Oracle and/or and/or itsits affiliates. affiliates. AllAll rights rights reserved. reserved. 33

34 NEW: Oracle Data Integration Platform Cloud Key Capabilit 1. Data High Availability ies: 2. Data Migrations 3. Data Warehouse Automation 4. Databus & Stream Integration 5. Data Governance

35 Flexible Packaging Solution Use Cases: Data Integration Platform Cloud Features: Standard Edition Enterprise Edition Governance Edition Database Migrations (offline) Bespoke Data Marts DW Automation (batch) Database E-LT & ETL Profiling & Lineage (basic) Intuitive Web Dashboard & Service Home Bulk Data Movement & Transformations Basic Profiling with SaaS & PaaS Connectivity Admin, Monitoring, Basic Governance Streaming Database Transactions Streaming ETL and Complex Transformations Native Big Data (stream/batch) Support Database Continuity Database Migrations (online) DW Automation (stream/batch) Real-time Reporting/Analytics Big Data ETL (stream/batch) Multi-Directional Database Replication Data Profiling (advanced) Data Cleansing (real-time/batch) Data Lineage (comprehensive) Audit and Repair, Workflow Advanced Business Glossary and Business Rules Comprehensive Data Profiling & Cleansing Compliance, Audit and Case Management Data Lineage Business, Vertical, Horizontal 35

36 Demo is on 36

37 37

38 Safe Harbor Statement The preceding is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, timing and price of any features or functionality described for Oracle's products may change and remains at the sole discretion of Oracle Corporation. Statements in this presentation relating to Oracle s future plans, expectations, beliefs, intentions and prospects are "forward-looking statements" and are subject to material risks and uncertainties. A detailed discussion of these factors and other risks that affect our business is contained in our SEC filings, including our most recent reports on Form 10-K and Form 10-Q, particularly under the heading "Risk Factors." Copies of these filings are available online from the SEC or by contacting Oracle Corporation s Investor Relations Department at (650) or by clicking on SEC Filings on Oracle s Investor Relations website at All information set forth in this presentation is current as of October 3rd, Oracle undertakes no duty to update any statement in light of new information or future events. 38

39 39

40