The world is changing

Agenda

- New challenges and ways

- On-premises or cloud (or both?)

- The union of all

- Making sense of it

- How to get there...

Today, 80% of

organizations

adopt c loud-fi rst

strategies

AI investment

increased by

300% in 2017

Data wi l l grow to

44 ZB in 2020

Today, 80% of

organizations

adopt c loud-fi rst

strategies

AI investment

increased by

300% in 2017

Data wi l l grow to

44 ZB in 2020 C LO U D A IDATA

C LO U D

DATA A I

Organizations that harness data, cloud, and AI outperform

Rely on a modern data estate

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

9

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...

The many sources and rapid growth of data requires a new approach

• Sentiment Analysis

• Social Media / Sales Connection

• Customer Segmentation

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

BUSINESS APPS

CUSTOM APPS

ANALYTICAL DASHBOARDSAZURE SQL DATA WAREHOUSE

AZURE CLI

AZURE DATA FACTORY

BCP COMMAND LINE UTILITY

SQL SERVER INTEGRATION SERVICES

AZURE ANALYSIS SERVICES

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

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

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)

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

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 MarketplaceHDP | CDH | MapR

Azure Data Lake

Analytics

IaaS Clusters Managed Clusters Big Data as-a-service

Azure HDInsight

Frictionless & Optimized

Spark clusters

Azure Databricks

BIG

DA

TA

S

TO

RA

GE

BIG

DA

TA

A

NA

LYT

ICS

Red

uced

Ad

min

istr

ati

on

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

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)

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

Microsoft BI, the agile way…

Azure

Analysis Services

Data Sources Ingest Prepare Analyze Publish Consume

Sensors and devices

StreamAnalytics

DiagnosticStreaming

Power BI

Sources- Oralce HFS- SAP BW- …

Azure Data Lake Store

Data Factory: Move data, orchestrate, schedule and monitor

Azure Data LakeIoT Hubs

MachineLearning

HDInsight

Data ScienceWorkbench

StreamAnalytics

Power BI Report Server

Architecture Blueprint

SSIS

SQL Server 2017: Security, Performance, Polybase, ML Services, Analytics

SQL Server2017

SSAS

BI Bot

Apps

Lab- and other Apps

Azu

re D

ata

Pla

tfo

rmSQ

L se

rver

20

17

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

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

Empower today’s innovators to unleash the power of data

and reimagine possibilities that will improve our world