Oracle Autonomous Data Warehouse

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1 Oracle Autonomous Data Warehouse Self-driving, Self-securing, Self-repairing Fekete Zoltán Principal Solution Engineer #thinkautonomous

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, and timing of any features or functionality described for Oracle s products remains at the sole discretion of Oracle. 2

3 Az Oracle ezt javasolja: Autonomous Database Self-Driving önvezető Kevesebb emberi hiba, kisebb költség, nagyobb produktivitás, ön-patchelés, ön-tuningolás, skálázás leállás nélkül Self-Securing önálló biztonság Védelem: külső támadások, ártó belső felhasználók ellen Patch-ek, titkosítás, Self-Repairing önjavító Automatikus védelem a leállások ellen

4 Autonomous a következő állomás az úton Teljes automatizálás az adatbázis életciklus menedzsmentben ORACLE AUTONOMOUS DATABASE Oracle Cloud Complete Infrastructure Automation Complete Database Automation Automated Data Center Operations and Machine Learning A világ első autonóm adatbázisa 4

5 Autonóm IT miért is lélegzik föl az üzlet? Miért jó ez Önnek? Boldog szakma-üzlet operatív munka innováció gyors út az elemzésekig gyorsabb adaptálás néhány kattintás és indul a motor: adatbetöltés több idő az önkiszolgáló üzleti elemzésekre fókusz: alkalmazások megtervezése, fejlesztése felhasználói élmény szervezet: jobb működés, hatékonyabb és biztonságosabb

6 Autonomous adatbázisok AUTONOMOUS DATABASE CLOUD Autonomous Data Warehouse Autonomous Transaction Processing DW betöltés másodpercek alatt Másodpercenként tranzakciók milliói Adatpiacok és adattárházak analitikával Működés-kritikus adatbázisok Sandbox-ok az adattudósoknak Adatbázis konszolidáció Data lakes: strukturált és strukturálatlan adatok Valós idejű tranzakció elemzés

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9 Automated Tuning Load and go Define tables, load data, run queries No tuning required No special database expertise required No need to worry about tablespaces, partitioning, compression, in-memory, indexes, parallel execution Fast performance out of the box with zero tuning Simple web-based monitoring console Built-in resource-management plans

10 Automated Reliability Fault-tolerant, highly-available Exadata infrastructure Triple-mirrored disks for disk failures Real Application Clusters for compute node failures And more Automatic backups Point in time recovery to anytime in last 60 days Online patches Regular patches applied with zero database downtime

11 Automated Security Always up-to-date on security patches Eliminates the largest security risk in current customermanaged systems Full encryption for entire database, backups and all network connections Database auditing always on Login failures Modifications to user accounts or database structures Secure by default Customers are unable to disable security configurations

12 Service Provisioning Network, Storage and Server Infrastructure OS Administration Backup and Restore Patching Service Continuity (HA) and Disaster Recovery Database Configuration and Tuning Security and Compliance User Management, Role and Permissions Database Schema Management Data Security Policies Data Loading and Integration BI Services and Tools Integration Cloud Services Management ADW Responsibility Customer Responsibility 12

13 Simplified Database User Management Every data warehouse initially created with an ADMIN user Additional users can be granted admin privilege as necessary DW developers/users should use DWROLE Simplified user creation via this new database role No need to specify anything except the password DWROLE includes all necessary privileges for a DW developer/user create user sh identified by sh; grant dwrole to sh;

14 Database Service Names 3 pre-defined database services Choice of performance and concurrency HIGH Highest resources, lowest concurrency Queries run in parallel MEDIUM Less resources, higher concurrency Queries run in parallel LOW Least resources, highest concurrency Queries run serially Example for a database with 16 OCPUs No of concurrent queries Max idle time CPU shares HIGH 3 5 mins 4 MEDIUM 20 5 mins 2 LOW 32 1 hour 1

15 Data Loading for ADW Data loading via SQL*Net Suitable for small volumes of data SQL*Loader from local filesystem ETL scripts that use DML to insert/update data Data loading from Oracle Object Storage Preferred technique for large volumes of data Additionally enables data-sharing with other cloud services Stage data in Oracle Object Storage, then load into the database using new PL/SQL APIs Follow best practices for DW data-loading Use bulk data operations, not row-by-row operations

16 Data Loading Example channels.csv "CHANNEL_ID","CHANNEL_DESC","CHANNEL_CLASS","CHANNEL_CLASS_ID","CHANNEL_TOTAL","CHANNEL_TOTAL_ID" 3,"Direct Sales","Direct",12,"Channel total",1 9,"Tele Sales","Direct",12,"Channel total",1 5,"Catalog","Indirect",13,"Channel total",1 4,"Internet","Indirect",13,"Channel total",1 2,"Partners","Others",14,"Channel total",1

17 External Table Example channels.csv "CHANNEL_ID","CHANNEL_DESC","CHANNEL_CLASS","CHANNEL_CLASS_ID","CHANNEL_TOTAL","CHANNEL_TOTAL_ID" 3,"Direct Sales","Direct",12,"Channel total",1 9,"Tele Sales","Direct",12,"Channel total",1 5,"Catalog","Indirect",13,"Channel total",1 4,"Internet","Indirect",13,"Channel total",1 2,"Partners","Others",14,"Channel total",1

18 Supported by a rich Data Warehouse Ecosystem Oracle Autonomous Data Warehouse supports: Existing tools running on-premise or in Oracle Cloud Oracle BI and data-integration tools 3 rd party BI tools 3 rd party data-integration tools Connectivity via SQL*Net Oracle Cloud Services Oracle Analytics Cloud Oracle Data Integration Platform Cloud and others

19 Oracle Data Visualization Desktop Self-service data exploration for business users Rich, interactive visualizations Included with ADW* Also available as cloud version within Oracle Analytics Cloud * May be be use with ADW at no added cost 19

20 OracleML: Built-in notebook Collaborative UI for data scientists Easy access to shared notebooks, templates, permissions, scheduler, etc. Based on Apache Zeppelin Roadmap: Common UI for data scientists across multiple services 20

21 Learn to develop with cloud services Cloud service console You can also manage cloud services via cloud API s and CLI Cloud API s provide full control over cloud services Every command available in service console (UI) is also available via API s Available interfaces: REST API CLI SDK s for Java, Python, etc 21

22 Location of the security credentials wallet

23 Próbálja ki az autonóm adatbázist! Keressen: Copyright 2018, Oracle and/or its affiliates. All rights reserved.

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25 Where to get more information Product information: cloud.oracle.com/datawarehouse Documentation ADW: Free Hands-on Workshops in the cloud Got a question? Try our new Q&A Forum on Cloud Customer Connect 25

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