Date post: | 07-Dec-2014 |
Category: |
Mobile |
Upload: | mobilemonday |
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Microsoft Azureand BI
Dr Christian Geuer-Pollmann
@chgeuer / chgeuer@microsoft
http://aka.ms/chgeuer
whiteboard
clown
cloud
architect
code
monkey
that’s me
Microsoft
Azure
Relational
Storage
Big
Data
The BI
landscape
microsoft azure
azure globally
dublin, ireland
53°19'28.7"N 6°27'17.2"W
a.k.a. azure region „Europe North“
how the satellite sees it
how a helicopter sees it
how a cab driver sees it
ping power pipe
(many)
containers
what‘s in it
azure ‘cloud services’ (PaaS)
cloud service instance
Cloud Services
virtual machines
Openness
web sites (SaaS)
ftp, git, …
http, https
web sites
web sites
mixing through VNETs
mixing PaaSand IaaSwith VNETs
SQL on Azure
A Server Is Not A Machine
Azure SQL Database
The Basics
Server Provisioning
SQL Server on IaaS
IaaS Workloads – all about the app
Line of Business Applications
Custom Applications, CRM, CMS, ERP, Business Intelligence
Application Infrastructure
File Servers, Databases, Identity, Source Control
Developer, Test and Staging Environments
Quickly Provision and Un-provision Entire Environments
Hybrid Applications
Applications that span your data center and the cloud
SQL Server or Windows Azure SQL DB?
• Network transport (Tabular Data Stream)
• SQL dialect (Transact-SQL)
• Data access APIs (ADO.NET, ODBC, JDBC)
• Development tools (SQL Server Data Tools)
• Management tools (SQL Server Management Studio)
SQL Server
(IaaS)
Azure SQL Database
(PaaS)
Development Migrate Existing Apps Develop New Apps
Management Full Control Managed Service
Compatibility Full SQL Server Capabilities Based on SQL Server Technology
Big Data
Traditional E-Commerce Data Flow
New E-Commerce Big Data Flow
MapReduce
So How Does It Work?
So How Does It Work?
Hadoop
Traditional RDBMS vs. MapReduce
The Hadoop Ecosystem
Connect Excel to Hadoop with Power Query
Connect Excel to Hadoop with the Microsoft Hive ODBC Driver
Detailed Offerings
Hadoop on WindowsInsights to all users by activating new types of data
Microsoft Big Data Solution
Machine Learning
Azure Portal
Azure Ops Team
ML Studio
Data Scientist
HDInsight
Azure Storage
Desktop Data
Azure Portal &
ML API service
Azure Ops Team
ML API service Developer
ML Studio
• Access and prepare data
• Create, test and train models
• Collaborate
• One click to stage for
production via the API service
Azure Portal & ML API service
• Create ML Studio workspace
• Assign storage account(s)
• Monitor ML consumption
• See alerts when model is ready
• Deploy models to web service
ML API service and the Developer
• Tested models available as an url that can be called from any end point
48
BI on Azure
BI on Azure
SQL on Azure
SQL Server(on IaaS)
Hadoop
SQL DB (as a Service)
Own Hadoop(on IaaS)
HDInsight(Hadoop as a Service)
APS(PDW)
Machine
Learning
Document
DB
Excel
PowerBI
Intelligent
Systems Service