1. Setting Big Data Capabilities Free How to Make Business on Big Data? Stig Torngaard, Partner Platon

2. Our facts © Platon consulting company A leading independent 170+ employees 500+ clients globally 1999 Founded in Employee-owned company 5 offices Nordic 2

3. Big Data - Why? Challenged from many sides REALTIME ENTERPRISE EXPLODING DATA VOLUMES FACING NEW COMPETITION THE INTERNET OF THINGS BUSINESS COMPLEXITY ANY DATA SOURCE FAST CHANGING WORLD

4. (Big) Data Sources Data volumes ERP Webshop Web Logs Emails Click Streams Likes Sensors Tweets TransactionsInteractionsObservations Data variety and complexity

5. The four V’s of Big Data = Any Data 5 VolumeVelocity VarietyVariability 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.

6. “BIG” DATA Information Use Cases Advanced Analytics Big Data Technologies Transactions 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-Memory Map/Reduce A Platon view on Big Data

7. Information use cases © Platon7 Understand customer sentimentsTest market responseIndividualize value proposition Target equipment maintenanceAutomate Application ProcessingPredict customer behavior

8. 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

9. 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

10. Platon Market Observation Information Management disciplines and especially Data Management are valuable core capabilities when engaging on a Big Data journey.

11. The fundamental (Data) Scientist requirement Any Data or Event Any Question Data independence Tool independence Loosely coupled

12. HDInsight; Hadoop for everyone in the Cloud

13. Analytics A Microsoft Big Data example Azure Blob Storage HDInsight (Compute) Azure DataMarket Excel PowerBI PowerQueryPowerMapPowerPivot Hive (SQL) Query HDInsight Content Odata feed Data Sources Upload data, streaming data Web Analytics Project XY Other data, Social etc.

14. Big Data Architecture Components Collaborate and stay connected Discover, analyze, and visualize with familiar tools Source: Microsoft

15. Reimaging the Intelligent Business Traditional Business Intelligence Imagine Information Use Cases Leverage new Technologies Design Hybrid Information Architecture Explore Any Data Next Level BI

16. 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)!

17. Platon Key Observation “Big Data is a major challenge to our toolsets, but the greatest challenge is to our imagination” Stig Torngaard Hammeken Partner Email: sto@platon.net Twitter: stigtorngaard

18. Reference data Customer Architecture Example © Platon18 On-Premise Marts/Models MANUAL RAW CSV Intermediate Mart STORE COPY TRANSFORM HIVE (LOAD) TRANSPOSE EXTRACT Databases HDInsight (Cloud) Excel Power BI R SQL Server Machine MatLab