Setting Big Data Capabilities FreeHow to Make Business on Big Data?

Stig Torngaard, Partner Platon

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Our facts

consulting companyA leading independent

170+employees

500+clients globally 1999

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Employee-owned company

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Nordic

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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

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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

HDInsight; Hadoop for everyone in the Cloud

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: sto@platon.netTwitter: stigtorngaard

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Referencedata

Customer Architecture Example

© Platon

On-PremiseMarts/Models

MANUAL

RAW CSVIntermediate

Mart

STORE

COPY

TRANSFORM

HIVE (LO

AD)

TRANSPOSE

EXTRACT

Databases

HDInsight(Cloud)

Excel Power BIR

SQL ServerMachine

MatLab