Azure Data Lake Analytics



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Transcription:

Azure Data Lake Analytics

Compose and orchestrate data services at scale Fully managed service to support orchestration of data movement and processing Connect to relational or non-relational data that is on-premises or in the cloud Single pane of glass to monitor and manage data processing pipelines. Publish to Power BI MapReduce Hive Pig C# Stored Procedures Azure Machine Learning Trusted data BI & analytics Microsoft Confidential Under Strict NDA

Elastic cloud data warehouse with proven SQL Server capabilities Elastic scale and performance Scales to petabytes of data Massively Parallel Processing Instant-on compute scales in seconds Query Relational / Non-Relational Powered by the cloud Get started in minutes Integrated with Azure ML, PowerBI & ADF Market Leading Price & Performance Simple billing compute & storage Pay for what you need, when you need it with dynamic pause

A hyper scale repository for big data analytics workloads Store any data in its native format without prior transformation Hadoop Distributed File System (HDFS) For The Cloud Enterprise grade security, availability and durability Optimized for massive throughput - No limits on file and account sizes Analytics Service U-SQL ` Analytics YARN HDInsight (managed Hadoop Clusters) WebHDFS Store

{ } schema free query JavaScript as a modern T-SQL tunable consistency Relational and hierarchical query of application defined JSON data. Support for SQL queries with transforms, projections and inline evaluation of user defined JavaScript functions (UDFs). Automatic and consistent indexing of all properties. Transactional execution of application defined stored procedures and triggers directly against database collections. Native JavaScript support eliminating the impedance mismatch (ORM) between application and database schema. Well defined consistency levels to achieve optimal tradeoff between consistency and performance. Four distinct consistency levels for queries and read Strong, Bounded-Staleness, Session and Eventual. Granular control over consistency, availability and latency fully managed Simple to provision and access databases without managing VM or cluster infrastructure. Operated with high availability and automatically backed up to prevent against regional failures.

Azure Machine Learning Powerful predictive analytics in Azure ML Algorithms are best of breed and embrace OSS MS + R + Python + BYOA ML Studio for productive development Faster experiments results in faster improvements Visual Workflows & ML Experiments at Cloud Scale ML Operationalization to remove deployment friction Build entire ML Apps & Deploy as Cloud APIs ML Applications Marketplace Provide ML applications like apps in an app store Publish/consume APIs in a 2 sided market Help organizations eliminate undifferentiated heavy lifting

Process real-time data in Azure using a simple SQL language Consumes millions of real-time events from Event Hub collected from devices, sensors, infrastructure, and applications Performs time-sensitive analysis using SQL-like language against multiple real-time streams and reference data Outputs to persistent stores, dashboards or back to devices PCs/ Laptops POS Terminals Self Checkout Stations Smart Phones Kiosks Slates/ Tablets Point of Service Devices Automation Devices Servers Digital Signs Logic Controllers ATM Security Thin Clients Remote Medical Monitors Vending Machines Handhelds Kinect Specialized Devices Diagnostic Equipment

A single pane of glass to view of the operation of your business Provides a real-time view of your business operations Direct connections to on-premise data supporting Hybrid scenarios Native ios, Android and Windows mobile apps Out of the box reports for a growing list of SaaS services empowering the end users Natively integrated with Microsoft applications, services and data platform..

Perceptual Intelligence Advanced algorithms for vision and speech Face APIs Speech APIs Computer Vision APIs Language Understanding Intelligent Service (LUIS)

Typical Architecture Event producers Collection Event Queuing System Transformation Long-term storage Presentation and action Applications Azure Machine Learning Azure Data Lake Mobile devices Devices Cloud gateways (web APIs) Event hubs Azure HDInsight Azure SQL DW Event hub Devices to take action Sensors Azure Stream Analytics Live Dashboards Web and social Field gateways Management Azure Data Factory Power BI

Azure Data Lake Analytics

1. Bring Your Own Data Insights 2. Bring Your Own Data Analytics 3. Bring Your Own Data Architecture 4. Bring Your Own Things Innovate Contact nlvip@microsoft.com to register for these workshops