The document discusses the transformation of organizations towards cloud-first strategies, highlighting the rapid growth of data and the significant increase in AI investments. It emphasizes the importance of a modern data estate, including data lakes, to manage various data types effectively for analytics and machine learning. Additionally, it outlines Microsoft's tools and services that facilitate data migration and business intelligence solutions in this evolving landscape.

1. The world is changing

2. Agenda
- New challenges and ways
- On-premises or cloud (or both?)
- The union of all
- Making sense of it
- How to get there...

3. Today, 80% of
organizations
adopt cloud-first
strategies
AI investment
increased by
300% in 2017
Data will grow to
44 ZB in 2020

4. Today, 80% of
organizations
adopt cloud-first
strategies
AI investment
increased by
300% in 2017
Data will grow to
44 ZB in 2020 C LO U D A IDATA

5. C LO U D
DATA A I
Organizations that harness data,
cloud, and AI outperform

6. Rely on a modern data estate

7. Patrik Borosch
TSP / DP
• 02.07.1971/married/Daughter(19)
• Music(Squared Circle/The Midcrise Liars)/climbing/skiing/cycling/Tango
• EDV-Kaufmann (german IHK 1995) = Data Processing with Cobol and Databases = the early BI
guys ;)
• Reporting and data processing in controlling departments
• BI Consultant/Senior Consultant: ASTECH Solutions/T-Systems/Trivadis/Avanade
•  Discipline Manager Microsoft BI and Power Pivot Trainer @ Trivadis
• Head of BI: Allianz Global Assistance
• TSP DP: Microsoft
• SQL Server/SSIS/SSAS/SSRS/MDM
• PowerBI/PowerPivot/PowerQuery
• Azure SQL DB/DW/Data Lake/Azure Stream Analytics/Data Factory/AAS
• SQL/DAX/MDX/(PowerShell)/(C#)
• Informatica/Microstrategy/Essbase/Enterprise Architect/UML/Perl/Unix/Linux  had that... been
there...
• First «Big Data»-Project in 2006: Teradata/Informatica/Microstrategy, 1.4TB = eight weeks for init
load = lots of fun :D

8. 8

9. 9

10. Dr. John Snow (1854)
One of the first visual
investigations of collected
data helped to solve a cholera
epidemic in Soho…
- You need the facts
- BUT you also need to
make sense of it...
Therefore you need to have
the right tools and methods...

11. The many
sources and
rapid growth
of data
requires a
new approach
• Sentiment
Analysis
• Social Media /
Sales
Connection
• Customer
Segmentation

12. Data lake
From Wikipedia, the free encyclopedia
A data lake is a method of storing data within a system or repository, in its natural format,[1] that
facilitates the collocation of data in various schemata and structural forms, usually object blobs or files.
The idea of data lake is to have a single store of all data in the enterprise ranging from raw data (which
implies exact copy of source system data) to transformed data which is used for various tasks including
reporting, visualization, analytics and machine learning. The data lake includes structured data from
relational databases (rows and columns), semi-structured data (CSV, logs, XML, JSON), unstructured
data (emails, documents, PDFs) and even binary data (images, audio, video) thus creating a centralized
data store accommodating all forms of data.
James Dixon / Pentaho (2010)
Data Lakes

13. BUSINESS APPS
CUSTOM APPS
ANALYTICAL DASHBOARDS
AZURE SQL DATA WAREHOUSE
AZURE CLI
AZURE DATA FACTORY
BCP COMMAND LINE UTILITY
SQL SERVER INTEGRATION SERVICES
AZURE ANALYSIS SERVICES

14. BUSINESS APPS
CUSTOM APPS
ANALYTICAL DASHBOARDS
DATA FACTORY
ANALYTICAL DASHBOARDS
Polybase
AZURE SQL DATA WAREHOUSE
DATA FACTORY
AZURE ANALYSIS SERVICES
AZURE MACHINE LEARNING
& MACHINE LEARNING SERVER
AZURE COSMOS DB
AZURE STORAGE

15. BUSINESS APPS
CUSTOM APPS
ANALYTICAL DASHBOARDS
DATA FACTORY
ANALYTICAL DASHBOARDS
Polybase
AZURE SQL DATA WAREHOUSE
DATA FACTORY
AZURE ANALYSIS SERVICES
AZURE MACHINE LEARNING
& MACHINE LEARNING SERVER
AZURE COSMOS DB
AZURE HDINSIGHT
(Hadoop)AZURE STORAGE

16. BUSINESS APPS
CUSTOM APPS
ANALYTICAL DASHBOARDS
DATA FACTORY
ANALYTICAL DASHBOARDS
Polybase
AZURE SQL DATA WAREHOUSE
DATA FACTORY
AZURE ANALYSIS SERVICES
AZURE MACHINE LEARNING
& MACHINE LEARNING SERVER
AZURE COSMOS DB
AZURE STORAGE AZURE DATABRICKS
(SPARK)

17. BUSINESS APPS
CUSTOM APPS
ANALYTICAL DASHBOARDS
DATA FACTORY
AZURE DATA LAKE STORE AZURE DATA LAKE ANALYTICS
ANALYTICAL DASHBOARDS
Polybase
AZURE SQL DATA WAREHOUSE
DATA FACTORY
AZURE ANALYSIS SERVICES
AZURE MACHINE LEARNING
& MACHINE LEARNING SERVER
AZURE COSMOS DB

19. CONTROL EASE OF USE
Azure Data Lake
Analytics
Azure Data Lake Store
Azure Storage
Any Hadoop technology,
any distribution
Workload optimized,
managed clusters
Data Engineering in a
Job-as-a-service model
Azure Marketplace
HDP | CDH | MapR
Azure Data Lake
Analytics
IaaS Clusters Managed Clusters Big Data as-a-service
Azure HDInsight
Frictionless & Optimized
Spark clusters
Azure Databricks
BIGDATA
STORAGE
BIGDATA
ANALYTICS
ReducedAdministration
K N O W I N G T H E V A R I O U S B I G D A T A S O L U T I O N S
Drag & Drop
Azure ML

20. Big Data is driving transformative changes
Cost
Culture
Data
Characteristics
Traditional Big Data
Relational
(with highly modeled schema)
All Data
(with schema agility)
Expensive
(storage and compute capacity)
Cloud
(storage and compute capacity)
Rear-view reporting
(using relational algebra)
Intelligent action
(using relational algebra AND ML,
graph, streaming, image processing)

21. Cognitive Services
• Faces, images, emotion recognition and video intelligence
• Spoken language processing, speaker recognition, custom speech recognition
• Natural language processing, sentiment and topics analysis, spelling errors
• Complex tasks processing, knowledge exploration,
intelligent recommendations
• Bing engine capabilities for Web, Autosuggest, Image,
Video and News
Intelligence
Cortana
Bot
Framework
Cognitive
Services

22. Microsoft BI, the agile way…
Azure
Analysis Services

24. Data Sources Ingest Prepare Analyze Publish Consume
Sensors
and devices
Stream
Analytics
Diagnostic
Streaming
Power BI
Sources
- Oralce HFS
- SAP BW
- …
Azure Data Lake Store
Data Factory: Move data, orchestrate, schedule and monitor
Azure Data LakeIoT Hubs
Machine
Learning
HDInsight
Data Science
Workbench
Stream
Analytics
Power BI Report Server
Architecture Blueprint
SSIS
SQL Server 2017: Security, Performance, Polybase, ML Services, Analytics
SQL Server
2017
SSAS
BI Bot
Apps
Lab- and
other Apps
AzureDataPlatformSQLserver2017

25. AI built-in | Most secure | Lowest TCO
M I C R O S O F T F O R Y O U R M O D E R N D A T A E S T A T E
Data warehouses
Data lakes
Operational databases
Data warehouses
Data lakes
Operational databases
SQL Server Azure Data Services
Industry leader 4 years in a row
#1 TPC-H performance
T-SQL query over any data
70% faster
2x the global reach
99.9% SLA
HYBRID
Easiest lift and shift
with no code changes
SocialLOB Graph IoTImageCRM
Security and
performance
Flexibility
of choice
Reason over
any data, anywhere

26. Tools for your
migration journey
SQL Server Migration Assistant (SSMA)
Automates database migration to SQL Server from
Microsoft Access, DB2, MySQL, Oracle, and SAP ASE.
Data Migration Assistant (DMA)
Enables upgrade to SQL Server and Azure SQL
Database.
Database Experimentation Assistant (DEA)
Assists in evaluating a targeted version of SQL for
a given workload.
Azure Hybrid Benefit for SQL Server
Maximizes current on-premises license investments
to facilitate migration.
Azure SQL Database Managed Instance
Facilitates lift and shift migration from
on-premises SQL Server to PaaS.
Azure Database Migration Service (Azure DMS)
SQL Server Migration Assistant (SSMA)
Data Migration Assistant (DMA)
Database Experimentation Assistant (DEA)
SQL Database
Managed Instance
Azure Hybrid
Benefit for
SQL Server

27. Empower today’s innovators to unleash the power of data
and reimagine possibilities that will improve our world