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© Platon
Our facts
consulting companyA leading independent
170+employees
500+clients globally 1999
Founded in
Employee-owned company
5offices
Nordic
2
Big Data - Why? Challenged from many sides
REALTIMEENTERPRISE
EXPLODINGDATA
VOLUMES
FACING NEW COMPETITION
THE INTERNET OF THINGS
BUSINESSCOMPLEXITY
ANY DATASOURCE
FAST CHANGING
WORLD
(Big) Data Sources D
ata
volu
mes
ERP
Webshop
Web Logs
Emails
Click Streams
Likes
Sensors
Tweets
Transactions Interactions Observations
Data variety and complexity
5
The four V’s of Big Data = Any Data
Volume Velocity
Variety Variability
Data explosion. Multi-layered architecture Non linear scalability.
Data changes rapidly. Events in new pace. Decision window.
Many data formats. Complex integration. Non structured sources.
Variable interpretations. Enriching existing views. Virtual models.
“BIG”DATA
Information Use Cases
Advanced Analytics
Big Data Technologies
Tran
sacti
ons Interactions
Observations
Decision engines
Complex Event Processing
Visualization
Data Mining
Information Retrieval
Create transparency
Enable experimentation
Customize actions
Automate decisions
Innovate new business model
MPP/Appliances
Streaming
Unstructured
In-MemoryMap/Reduce
A Platon view on Big Data
© Platon
Information use cases
7
Understand customer sentiments Test market response Individualize value proposition
Target equipment maintenance Automate Application Processing Predict customer behavior
Case: Karnov, Better BI using Big Data
• A Digital Transformation, from books to services
• Statistics on usage and recommendation
• Integrate any data source
– JSON
– SAP
Transform
Case: Data-driven innovation at Chr. Hansen R&D
• From one-man armies to Collaborative Data in R&D
• “Setting data free”, M. Meldgaard
• Automatic data capture
• Downscaling theme
• Finer data granularity
• Rethinking R&D
Platon Market ObservationInformation Management disciplines and especially Data Management are valuable core capabilities when engaging on a Big Data journey.
The fundamental (Data) Scientist requirement
Any Data or Event
Any Question
Data independence
Tool independence
Loosely coupled
Anal
ytics
A Microsoft Big Data example
Azure Blob Storage
HDInsight (Compute)
Azure DataMarket
Excel PowerBI
PowerQuery PowerMap PowerPivot
Hive (SQL) QueryHDInsight Content Odata feed
Dat
a So
urce
s
Upload data, streaming data
Web Analytics
Project X Y
Other data, Social etc.
Big Data Architecture Components
Collaborate and stay connected
Discover, analyze, and visualize with familiar tools
Source: Microsoft
Reimaging the Intelligent Business
Traditional Business Intelligence
Imagine Information Use Cases
Leverage new Technologies
Design Hybrid Information Architecture
Explore Any Data
Next Level BI
Big Data is here to stay
• Big Data is Disruptive and will change the way we all do business
– Not just ”BIG” data (like Volume) – but a focus on ANY data
– Cheap storage and “any data availability” means ______ to my business
• Understand and leverage technologies – and set them free
– Don’t replace your Data Warehouse. Big Data, it’s a complement
– (Advanced) Analytics loves Big Data – but you need a business goal
• Data-Driven Innovation, it’s a Business Strategy Update!
– Get 90% of your inspiration from other industries
– Data is the new Business ”fuel”
– Rethink your business (as well as some IT)!
Platon Key Observation“Big Data is a major challenge to our toolsets, but the greatest challenge is to our imagination”
Stig Torngaard HammekenPartner
Email: [email protected]: stigtorngaard