This document discusses big data and how organizations can gain insights from data. It notes that by 2015, organizations that have built a modern information system will financially exceed their competitors by 20%. It describes different types of structured and unstructured data organizations are dealing with, including machine-generated data from sensors, satellites, science experiments, videos, and more. It also lists common uses of big data like recommendations, smart meter monitoring, equipment monitoring, advertising analysis, and more. The document then discusses how Microsoft can help users gain better insights through self-service BI, connecting and collaborating in Office 365, and answering questions. It outlines different data sources including non-relational data stored in HDInsight on Azure.

2. larsBG@microsoft.com
Big Data. Small data. All data.

3. Mark Beyer, Gartner
(Information Management in the 21st Century)
”By 2015 will organizations that has built a
modern information system financially exceed
it’s competitors with 20%"

4. Anticipatory
shipping

7. Data Complexity: Variety and Velocity
Terabytes
Gigabytes
Megabytes
Petabytes

8. Machine-generated unstructured data:
• Sensor data: This includes all kind of devices providing data.
• Satellite images: This includes weather data or satellite surveillance imagery. Just think about BING MAPS
or Google Earth, and you get the picture.
• Scientific data: This includes seismic imagery, atmospheric data, and high energy physics.
• Photographs and video: This includes security, surveillance, and traffic video.
• Radar or sonar data: This includes vehicular, meteorological, and oceanographic seismic profiles.
Human-generated unstructured data:
• Text internal to your company: Think of all the text within documents, logs, survey results, and e-mails.
Enterprise information represents a large percent of the text information in the world today.
• Social media data: This data is generated from the social media platforms such as YouTube, Facebook,
Twitter, LinkedIn, and Flickr.
• Mobile data: This includes data such as text messages and location information.
• Website content: This comes from any site delivering unstructured content, like YouTube, Flickr, or
Instagram.

9. Big Data is everywhere
Recommenda-tion
engines
Smart meter
monitoring
Equipment
monitoringAdvertising analysis
Life sciences
research
Fraud
detection
Healthcare
outcomes
Weather forecasting
for business
planningOil & Gas exploration
Social network
analysis
Churn
analysis
Traffic flow
optimization
IT infrastructure &
Web App
optimization
Legal
discovery and
document archiving
Intelligence
Gathering
Location-based
tracking & services
Pricing Analysis
Personalized
Insurance

10. Hvordan kan
Microsoft så
hjælpe dig med
at få bedre
indsigt ?

11. Self-Service BI
Self-service BI with the familiarity of Office and the power of the cloud

12. Empower users with self-service in Excel

13. Connect and collaborate in Office 365
Q&A

15. 15
Data sources

16. 16
Data sourcesNon-Relational Data

18. • HDInsight er Microsoft implementering af Hadoop™
• HDInsight er en service til at håndterer store mængder ustruktureret
data (og ustruktureret )
• Fuldt integreret til vores BI stak (f.eks. PowerQuery)
• HDInsight anvendes på 2 måder gennem Microsoft
– SQL Server Parallel DataWare House (on prem)
– Azure HDInsight service (Cloud)

19. Parallel Data Warehouse
• Shared-nothing parallel database system
» Massively parallel processing (MPP)
» A “Control” server that accepts user queries, generates a plan, and distributes operations
in parallel to compute nodes
» Multiple “Compute” servers running SQL Server
» A “Management” server for administering the system
» A “Data Movement Service” that facilitates parallel SQL operations
• Delivered as an appliance
» Balanced and pre-configured software and industry standard hardware from Dell and HP
» Single Call Support
» Fastest Time to Market
» Scales from 2 to 56 Nodes

20. www.windowsazure.com

21. Where should you start?

22. 8 April
CrownPlaza, København
www.conferencemanager.dk/businessin
sight2014

23. Resume
• Demo senarier
• 40 års aktiehandler (hurtig indsigt i industrier)
• Chicago Narcotics (data visualisering) + Trick or Treat (Hvor skal vores børn
hen og hente slik)
• Power BI (Deling af rapporter, samt ASK)
• Værktøjer
• Excel ( PowerQuery, PowerMAP)
• Power BI App – Windows 8
• Power BI med ASK i Office 365
• PDW eller Azure for HDInsight
• Hvilke scenarier giver værdi for jer ?
• Visualiser jeres data og gem nye data.
• Bliver I ”Master of data” ? (BigData )

24. .