2. http://GUSS.Pro @GUSS_FRANCE
Rejoignez la communauté
Webcasts, Conférences, Afterworks
La communauté
Data Microsoft
@GUSS_FRANCE /GUSS /GUSS.FR
Save the Date
Samedi 25 juin 2016
Campus SUPINFO
Tour Montparnasse, Paris
3. http://GUSS.Pro @GUSS_FRANCE
Préconférence
Cortana Analytics,
une plate-forme de données
moderne
Vendredi 24 juin 2016
En préambule du SQLSaturday Paris
Jean-Pierre Riehl – FR
MVP DataPlatform depuis 2008
@djeepy1
Fabien Adato – FR
Consultant Data Science
@fabienAD
4. http://GUSS.Pro @GUSS_FRANCE
Qui sommes nous ?
Jean-Pierre Riehl
Practice Manager Data & BI
MVP SQL Server
Chapter Leader– GUSS
@djeepy1
http://blog.djeepy1.net
Fabien Adato
Consultant Data Science
@fabienAD
http://fadata-blog.com
9. http://GUSS.Pro @GUSS_FRANCE
Cortana Analytics Suite
Transform data into intelligent action
Business
apps
Custom
apps
Sensors
and devices
People
Automated
Systems
Data Collection ToolsData Collection Tools
10. http://GUSS.Pro @GUSS_FRANCE
Boite à outils « Cloud »
HDInsight
Azure Data
Lake
Azure SQL
DWH
HADOOP
Azure
DocumentDB
Azure SQL
IaaS
Power BI
Azure Data
Catalog
Azure Machine
Learning
Azure Data
Factory
Azure Stream
Analytics
15. http://GUSS.Pro @GUSS_FRANCE
A hyper scale repository for big data analytic workloads
Introducing Azure Data Lake
• Hadoop File System compatible with
HDFS™
• Integrated with HDInsight, Revolution
R, Hortonworks, Cloudera
• Based on YARN
• Petabyte-sized files
• No size limits to data in single account
• Massive throughput to increase
performance
• AAD based access control
• Data management
Devices
19. http://GUSS.Pro @GUSS_FRANCE
Azure Machine Learning
• Data Mining 2.0
– De nombreux model de classification, régression et
clustering disponibles : Réseau de neurones, arbre de
décision, Support vector machine…
• Données en entrée
– HDInsight (Hive)
– Azure SQL
– Azure Tables
– Données locales (fichiers)
Azure Machine
Learning
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Azure Machine Learning
• Support de R et Python
• Requêtable par Web Service
– Azure ML API
• ML Studio Principe de la paillasse de
laboratoire
– Démarrage immédiat
Azure Machine
Learning
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Azure Stream Analytics
• Permet d’analyser des flux temps réel
– Millions d’événements / seconde
– 365 jours de rétention (ou 20To)
• Basé sur Event Hub
• Syntaxe SQL
• Export vers SQL Azure/Blob/Power BI/ADL…
Azure Stream
Analytics
SELECT Category, COUNT(*)
FROM Input TIMESTAMP BY EntryTime
GROUP BY
Category,
SlidingWindow(minute, 5)
34. http://GUSS.Pro @GUSS_FRANCE
Cortana Analytics Suite
Transform data into intelligent action
Business
apps
Custom
apps
Sensors
and devices
People
Automated
Systems
Data Collection ToolsData Collection Tools
Et tout cela dans un monde où tout va toujours de + en + vite time to market
Cortana Analytics Suite delivers an end-to-end platform with integrated and comprehensive set of tools and services to help you build intelligent applications that let you easily take advantage of Advanced Analytics.
First Cortana Analytics Suite provides services to bring data in, so that you can analyze it. It provides information management capabilities like Azure Data Factory so that you can pull data from any source (relational DB like SQL or non-relational ones like your Hadoop cluster) in an automated and scheduled way, while performing the necessary data transforms (like setting certain data colums as dates vs. currency etc). Think ETL (Extract, Transform, Load) in the cloud. Event hub does the same for IoT type ingestion of data that streams in from lots of end points.
The data brought in then can be persisted in flexible big data storage services like Data Lake and Azure SQL DW.
You can then use a wide range of analytics services from Azure ML to Azure HDInsight to Azure Stream Analytics to analyze the data that are stored in the big data storage. This means you can create analytics services and models specific to your business need (say real time demand forecasting).
The resultant analytics services and models created by taking these steps can then be surfaced as interactive dashboards and visualizations via Power BI
These same analytics services and models created can also be integrated into various different UI (web apps or mobile apps or rich client apps) as well as via integrations with Cortana, so end users can naturally interact with them via speech etc., and so that end users can get proactively be notified by Cortana if the analytics model finds a new anomaly (unusual growth in certain product purchases- in the case of real time demand forecasting example given above) or whatever deserves the attention of the business users.
Cluster Hadoop
Hbase NoSQL (ex : Key/Value Store)
Storm Real-time, basé sur des streams (des spouts et des bolts)
Cortana Analytics Suite delivers an end-to-end platform with integrated and comprehensive set of tools and services to help you build intelligent applications that let you easily take advantage of Advanced Analytics.
First Cortana Analytics Suite provides services to bring data in, so that you can analyze it. It provides information management capabilities like Azure Data Factory so that you can pull data from any source (relational DB like SQL or non-relational ones like your Hadoop cluster) in an automated and scheduled way, while performing the necessary data transforms (like setting certain data colums as dates vs. currency etc). Think ETL (Extract, Transform, Load) in the cloud. Event hub does the same for IoT type ingestion of data that streams in from lots of end points.
The data brought in then can be persisted in flexible big data storage services like Data Lake and Azure SQL DW.
You can then use a wide range of analytics services from Azure ML to Azure HDInsight to Azure Stream Analytics to analyze the data that are stored in the big data storage. This means you can create analytics services and models specific to your business need (say real time demand forecasting).
The resultant analytics services and models created by taking these steps can then be surfaced as interactive dashboards and visualizations via Power BI
These same analytics services and models created can also be integrated into various different UI (web apps or mobile apps or rich client apps) as well as via integrations with Cortana, so end users can naturally interact with them via speech etc., and so that end users can get proactively be notified by Cortana if the analytics model finds a new anomaly (unusual growth in certain product purchases- in the case of real time demand forecasting example given above) or whatever deserves the attention of the business users.