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Unleash the power of Big Data in your existing Data Warehouse
The document discusses leveraging big data in legacy data warehouses. It introduces Harro M. Wiersma, a big data expert, and outlines some of the challenges with traditional data warehouses, including inflexibility and multiple sources of data. The document then presents the concept of a big data data warehouse (bDWH), which aims to simplify infrastructure and bring big data into the existing warehouse to gain a 360-degree view of customers and businesses by leveraging various new sources of data.
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Unleash the power of Big Data in your existing Data Warehouse
- 1. WHT/082311 Unleash the power of Big Data in your legacy Data Warehouse Harro M. Wiersma M.Sc. Big Data Guy
- 2. WHT/082311 § HarroM. Wiersma § born 1976 in Groningen, the Netherlands § Master of Science – University of Phoenix (AZ) Computer Information Systems § past: contractor (DBA / Project Management / Team Management) § Manager Database IKEA / Technical Lead Infrastructure Engineering Sunrise / § Department Head Service Engineering Opitz Consulting CH § Head of IT Data Warehouse at PostFinance § current: Big Data Guy – looking for nice challenges § main focus area‘s: Telecom, Finance and Retail. § hobby‘s: golf, whisky, freelance sound engineer and tv producer. § contact: h@rro.wiersma.info WHO AM I © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 3. WHT/082311 MAIN PROBLEM – A CLEAR VIEW how can we prevent to get different results from different systems about the same KPI’s? how can we use our own data to support our opera+onal processes? © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 4. WHT/082311 KEEP A STRAIGHT FOCUS © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 5. WHT/082311 BIG DATA OR RIGHT DATA I‘m not interested in technology. I‘m not interested in data. I am interested in translaRng data into informaRon for decision making. © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 6. WHT/082311 MORE DATA, WAY MORE DATA © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 7. WHT/082311 TRACK TWEETS ... © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 8. WHT/082311 TRACK EMOTIONS ... © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich www.realeyesit.com
- 9. WHT/082311 TRACK MOVEMENTS ... © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich www.retailnext.net
- 10. WHT/082311 CURRENT DWH CHALLENGES § load-to-report, very unflexibile § longer nightly loads – is the night still long enough? § does the project-requester still now why (s)he needed the data when finally delivered, or has an alternative solution been created in the meanwhilea? § several different „sources-of-truth“ ... § how can we process these vast amounts of data? § how to implement new sources of untraditional data? © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 11. WHT/082311 BIG DATA CHALLENGES © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 12. WHT/082311 bDWH – BRINGING BUSINESS AND IT STRATEGIES TOGETHER Leveraging untradiRonal sources, social media and transacRonal data to gain the elusive 360 degree view of the customer and your business. © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 13. WHT/082311 TRADITIONAL DWH INFRASTRUCTURE © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 14. WHT/082311 TRADITIONAL DWH INFRASTRUCTURE © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 15. WHT/082311 LET’S SIMPLIFY THIS MESS … © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 16. WHT/082311 … AND BRING BIG DATA INTO THE WAREHOUSE © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 17. WHT/082311 THE POWER OF BIG DATA – THE bDWH CONCEPT © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 18. WHT/082311 § IT does knows data and infrastructure (only) § Business knows the intelligence to be applied to the data to derive value § Business knows how to discover data pa;erns (manual and automated) – Data ScienRsts § Business understands their seman+cs beVer § Business can perform data interroga+on in an experiment and associate rules of engagement early on for data usefulness § IT can create reusable reports of these experimental results. § Business can siX the data to curate the context § Big Data needs to be curated to be useful The bDWH concept brings Business and IT together to create added value IN WHAT DOES THE bDWH CONCEPT DIFFER © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 19. WHT/082311 THE bDWH PARADIGM CHANGE © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 20. WHT/082311 THE COMPLETE bDWH VALUE CHAIN 20 Collec+on – Structured, unstructured and semi-‐structured data from mulRple sources Inges+on – loading vast amounts of data onto a single data hub Discovery & Cleansing – understanding format and content; clean up and forma[ng Integra+on – linking, enRty extracRon, enRty resoluRon, indexing and data fusion Analysis – Intelligence, staRsRcs, predicRve and text analyRcs, machine learning Delivery – querying, visualizaRon, real Rme delivery on enterprise-‐class availability Collec+on Inges+on Discovery & Cleansing Integra+on Analysis Delivery © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 21. WHT/082311 KEY SUCCES FACTORS § Business needs to drive and execute the bDWH program § Data colloca+on and discovery is the most cri+cal step § Metadata is needed to process the data prior and post bDWH integraRon § Data quality can be processed by integraRng taxonomies § Data visualiza+on is needed to discover data § Metrics and metadata will be the bridge to integrate to the bDWH § Centralized infrastructure is needed to create a data-‐hub © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 22. WHT/082311 § Bring together exis+ng internal knowhow, combine it with external knowhow. don‘t silo your teams. § It‘s not about hardware, it‘s about the concept and way of thinking. § Reusable data, but which data is the ‚sole truth‘? § Who owns your data? do they really want to have transparency? § Are we allowed to use our data as we would like to? § Think of new and future business-‐concepts to be supported. FIRST STEPS © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 23. WHT/082311 The challenge facing the business today is the ability to influence the buyer decisions in a window of opportunity that does not last long. The analyRcs available at a personalizaRon level drives the buyer whether it is choosing a Doctor or buying a new laptop. To compete in this new era, businesses need to be driven by data and analyRcs, which are largely different from tradiRonal transacRons and campaigns! Both the “GeneraRon Z” and “Millennial GeneraRon” of buyers will not be swayed by tradiRonal engagement models of selling products and services! FROM TRANSACTIONAL TO BEHAVIOURAL © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 24. WHT/082311 PREDICTIVE BUSINESS INTELLIGENCE – DATA ANALYSIS § you know what you know – perfect, use it! § you know what you don‘t know – learn § you don‘t know what you know – invesRgate § you don‘t know what you don‘t know – find someone who does! © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 25. WHT/082311 § Do not try to implement without integraRon in your current landscape § Find a easy target, for example your data-‐archive § Collabora+on is key! Learn from other industries § Create cross-‐func+onal teams: IT – Analysts – Business § Champion business value: a ROI is there! § OrganizaRons that don’t leverage the big data that they have, risk losing ground to their compeRtors § Get on it, now! TAKE AWAYS © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 26. WHT/082311 This isthe moment… Are you ready? Big Data is a Game Changer © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 27. WHT/082311 QUESTIONS & ANSWERS Harro M. Wiersma M.Sc. h@rro.wiersma.info © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 28. WHT/082311 REFERENCE CASE I -‐ FINANCE § no fixed card-‐limit § acRve transacRon monitoring based on: § customer profile § credit raRng firms (4! in the USA) § acRve balance § payment history § result: lower security: payment in profile: only signature, otherwise: pincode or direct contact by phone with AmEx § result: less reversed transacRons (<3%) -‐> lower costs! § result: beVer insight in customers spending -‐> predicRve analyRcs! © 2013 Harro M. Wiersma – 23 September 2013 – Swiss Big Data Usergroup Zürich
- 29. WHT/082311 REFERENCE CASE II -‐ LOGISTICS