いそがしいひとのための Microsoft Ignite 2018 最新情報 Data 編
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いそがしいひとのための Microsoft Ignite 2018 最新情報 Data 編
- 1. いそがしいひとのための Microsoft Ignite 2018 + 最新情報 Data 編 山本 美穂 2018年10月15日 日本マイクロソフト 株式会社 パートナーソリューションプロフェッショナル
- 3. 本日のおしながき
- 4. Data 発表内容 +
- 9. Relationships Skills Professional contacts Job History Talent Meetings Documents Calendar Email Tasks Message People Storage Forecast Equipment maintenance Accounts Opportunities Service requests Orders Support case Shipments + Office 365+ LinkedInDynamics 365
- 10. Patients Merchandise Trade promotion Planograms Device data Forecast Equipment maintenance Accounts Opportunities Service requests Orders Support case Shipments Meetings Documents Calendar Email Tasks Message People Storage Relationships Skills Professional contacts Job History Talent + Office 365+ LinkedIn + Partner Solutions ( )Dynamics 365
- 11. + Office 365+ LinkedIn + Partner Solutions ( )Dynamics 365 Patients Merchandise Trade promotion Planograms Device data Forecast Equipment maintenance Accounts Opportunities Service requests Orders Support case Shipments Meetings Documents Calendar Email Tasks Message People Storage Relationships Skills Professional contacts Job History Talent
- 13. 2019/7/9 End of Support
- 18. SSMS 18.0
- 20. オンプレ RDBMS 連動 ETL PaaS RDB IaaS + PaaS NoSQL https://azure.microsoft.com/ja-jp/product-categories/databases/
- 21. オンプレ RDBMS 連動 ETL PaaS RDB IaaS + PaaS NoSQL https://azure.microsoft.com/ja-jp/product-categories/databases/ Azure Database for MariaDB Azure SQL Database Managed Instance
- 22. • Public preview of Intelligent Performance (Query Store, Performance Recommendation, and Query Insights) for PostgreSQL learns your unique database patterns and provides customized recommendations and insights that enable you to maximize the performance • Public preview of Advanced Threat Protection for MySQL and PostgreSQL monitors your database around-the-clock and detects potential malicious activities • Public preview of Azure Database for MariaDB brings fully- managed, open source MariaDB database-as-a-service to the Azure platform
- 26. Capability Service tier General Purpose (GA) Business Critical (Public Preview) Best for Apps with typical availability and common IO latency requirements Apps with highest availability and lowest IO latency requirements. Compute (vCores) 8, 16, 24, 34, 40, 64, 80 8, 16, 24, 34, 40, 64, 80 HA / Recovery Time Objective Remote storage based / Good Always On AG based / Better Storage type / size Fast remote (Azure Premium) / Up to 8 TB Super-fast local SSD / Up to 4 TB Read scale out (read-only replica) No Yes In-Memory OLTP No Yes Price competitive with AWS? Yes, ~33% lower (license included) Yes, ~46% lower (license included)
- 30. 4 TB 100 TB
- 33. Hyperscale is built based on a new cloud-born architecture which decouples compute, log and storage. Data Pages Data Pages Data Pages File Snapshots File Snapshots File Snapshots Log Cache Log ServiceLanding Zone (Azure Premium Storage) Long Term Storage for PITR (Azure Standard Storage)
- 34. PRODUCT ANNOUNCEMENT SQL Database • SQL Database Managed Instance (GA) • SQL Database Hyperscale (preview) • Reserved capacity (GA) • Advanced Threat Protection • Vulnerability Assessment GA • Data Classification and discovery public preview • Always Encrypted with Secure Enclave • Intelligent Database • SQL Graph enhancements • Intelligent QP enhancements • Approximate QP • Enterprise reliability • Accelerated Database Recovery • Parallel PFS updates • Resumable online index create/rebuild Azure Database Migration Service • Online migration to MI (preview) • Online migration to Azure Database for PostgreSQL/ MySQL (preview) • Offline migration to MI (GA)
- 41. 70+ Connectors Cost-effective Best Spark Fastest DW Modern BI
- 42. • Performance at any scale: SQL DW Compute Optimized Gen2 tier’s performance improvements become more accessible with a smaller SKU; DW500c. The performance-oriented tier is now also available across 26 global regions including Azure Government. • Streaming solutions: Build real-time analytics solutions with the best Databricks integration in the industry and easily stream, train and publish streaming dataframes on Azure. • Ease of use: Customers can now choose a preferred maintenance window based on their workstreams. They also get intelligent performance insights within the Azure portal and can create rich, customizable dashboard widgets with SQL Operations Studio. They also get accelerated and flexible restore points for enhanced data protection and recovery. • Enhanced security: They can also continuously monitor security and policy enforcement with SQL Vulnerability Assessment.
- 44. ETL / ELT Visual Authoring Azure Databricks Transform At Scale
- 45. ETL / ELT
- 48. Easy to ingest the data and easy to query the data Blob & Azure Queue Python SDK IoT Hub .NET SDK Azure Data Explorer REST API Event Hub .NET SDK Python SDK Web UI Desktop App Jupyter Magic APIs UX Power BI Direct Query Microsoft Flow Azure App Logic Connectors Grafana (coming soon) ADF (coming soon) MS-TDS Java SDK Java Script Monaco IDE Azure Notebooks Protocols Streaming Bulk APIs Blob & Event Grid Queued Ingestion Direct Java SDK
- 49. • Azure Data Explorer website – http://aka.ms/AzureDataExplorer https://aka.ms/ADEDocs http://aka.ms/ADEQuery http://aka.ms/ADEPortal http://aka.ms/ADEFeedback http://aka.ms/ADECommunity http://aka.ms/ADECalculator http://aka.ms/KQLPluralsight
- 50. • The most trusted and compliant platform A secure and managed Hadoop and Spark cloud platform for building data lakes for enterprises
- 52. Azure Data Lake Storage Logs (unstructured) Media (unstructured) Files (unstructured) Business/custom apps (structured) Apache Hive LLAP for interactive querying Azure HDInsight VS Code / JDBC Client New in Hive LLAP 3.0 • Result Caching • Dynamic Materialized Views • Workload Management • JDBC Integration
- 54. Advantages • ACID (Atomicity, Consistency, Isolation, and Durability) is default in Hive 3.0 • No Performance overhead • No Bucketing required • Spark can read and write to Hive ACID tables via Hive Warehouse connector
- 56. BRK2371 - Gaining deeper insights from big data using open source analytics on Azure HDInsight
- 57. WN WN WN WN WN HN HN Azure Data Lake Storage INSTANCE CORE RAM TEMP SSD D1 v2 1 3.50 GiB 50 GiB D2 v2 2 7.00 GiB 100 GiB D3 v2 4 14.00 GiB 200 GiB D4 v2 8 28.00 GiB 400 GiB D5 v2 16 56.00 GiB 800 GiB • Significant Spark performance speed up with IO cache (up to 9X perf gains) • Automatic cache resource management • DRAM + Temp SSD makes large cache pool
- 58. まとめ
- 59. まとめ
- 60. © 2018 Microsoft Corporation. All rights reserved. 本情報の内容（添付文書、リンク先などを含む）は、作成日時点でのものであり、予告なく変更される場合があります。 本書に記載した情報は、本書各項目に関する発行日現在の Microsoft の見解を表明するものです。Microsoftは絶えず変化する市場に対応しなければならないため、ここに記載した情報に対していかなる責 務を負うものではなく、 提示された情報の信憑性については保証できません。 本書は情報提供のみを目的としています。 Microsoft は、明示的または暗示的を問わず、本書にいかなる保証も与えるものではありません。 すべての当該著作権法を遵守することはお客様の責務です。Microsoftの書面による明確な許可なく、本書の如何なる部分についても、転載や検索システムへの格納または挿入を行うことは、どのような形 式または手段（電子的、 機械的、複写、レコーディング、その他）、および目的であっても禁じられています。 これらは著作権保護された権利を制限するものではありません。 Microsoftは、本書の内容を保護する特許、特許出願書、商標、著作権、またはその他の知的財産権を保有する場合があります。Microsoftから書面によるライセンス契約が明確に供給される場合を除いて、 本書の提供はこれらの特許、商標、著作権、またはその他の知的財産へのライセンスを与えるものではありません。 Microsoft, Windows, その他本文中に登場した各製品名は、Microsoft Corporation の米国およびその他の国における登録商標または商標です。 その他、記載されている会社名および製品名は、一般に各社の商標です。
- 70. Machine Learning