Post on 20-May-2020
Microsoft
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Centers
Experience the
Microsoft CloudMicrosoft
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CentersExperience the
Microsoft Cloud
Azure ML Data Camp
Ivan KosyakovMTC Architect, Ph.D.
Big Data
(3v)
Strategic
Analytics
Business Unit
Analytics
End User
Analytics
Advanced
Analytics
AnalystIT
Data Scientist
Top Manager
Business User
Microsoft
Technology
Centers
Experience the
Microsoft Cloud
Modern Data Warehouse
Analyst
IT
ActiveDirectory
Multi-FactorAuthentication
Key Vault
Customer
Data Scientist
Security Officer
Top Manager
Office 365
Business User
Developer
Hyperscalability
Most comprehensive
Unparalleled security
Intelligent by design
Transform data into intelligent action in the cloud
Information Management
Preconfigured Solutions
Dashboards and Visualizations
Machine Learning and Analytics
Big Data Store
Personal Digital Assistant – Cortana
Perceptual IntelligenceText AnalyticsComputer Vision APIs
Speech APIsFace APIs
Cortana Analytics Suite
Big Data Flow
Business apps
Custom apps
Sensors and devices
People
Machine Learning
and Analytics
Big Data Stores
Action
People
Automated Systems
Apps
Web
Mobile
Bots
Intelligence
Dashboards &
Visualizations
Cortana
Bot
Framework
Cognitive
Services
Power BI
Information
Management
Event Hubs
Data Catalog
Data Factory
HDInsight (Hadoop and Spark)
Stream Analytics
Intelligence
Data Lake
Analytics
Machine
Learning
SQL Data
Warehouse
Data Lake Store
Data Sources
Apps
Sensors and devices
Data
Big Data as part of Cortana IntelligenceMICROSOFT BIG DATA SOLUTIONS
Example reference architecture
Analyze Data Stored in Azure
• Track realtime data from IOT Suite: collect data from IOT
Suite in permanent store (ADLS)
• Track other Azure data (Azure Website generating web
logs) and store in ADLS
• Run Machine Learning through R Server for HDInsight to
find patterns in data
• Show results in BI tools (Power BI)
Real-Time
Reference architecture for Big Data
Data Generation Visualizations
SSRS
SharePoint BI
Excel BI
Power BI
Azure
Marketplace
ProcessingStorage
R ServerHive
Oozie
Sqoop Pig
SQL Server
Analysis Services
Azure HDInsight
Azure Machine
Learning
Azure
Document DB
Azure
SQL DB
HBase on Azure
HDInsight
Azure
Website
Azure Data Factory
Spark SQL
Spark MLib
Datazen
Azure
SQL DW
Azure Data
Lake Analytics
Azure Data Lake Store
Storm
for Azure
HDInsight
Azure
Stream
Analytics
Spark
Streaming
for Azure
HDInsight
Azure
Event
Hubs
Sensors
Bots
Crawlers
Devices
Microsoft
Technology
Centers
Experience the
Microsoft Cloud
Big Data Decision Tree
Source: https://biz-excellence.com/2016/08/30/big-data-dt
Big Data is often described as a solution to the “three V’s problem”, and how we choose right solution depends on which one of these problems we are trying to solve first:
Volume: need to store and query hundreds of terabytes of data or more, and the total volume is growing. Processing systems must be scalable to handle increasing volumes of data, typically by scaling out across multiple machines.
Velocity: need to collect data at an increasing rate from many new types of devices, from a fast-growing number of users, and from an increasing number of devices and applications per user. Processing systems must be able to return results within an acceptable timeframe, often almost in real-time.
Variety: situation when data do not match any existing data schema – semi-structured or unstructured data.
APIML STUDIO
10
SQL ServerR Services
Red Hat SUSE
Hadoop Teradata
Windows
CommercialCommunity
R ServerR Open
Cognitive
Services
Give your solutions
a human side
Microsoft
Technology
Centers
Experience the
Microsoft Cloud
Machine Learning Decision Tree
Source: https://biz-excellence.com/2016/09/13/machine-learning-dt