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DATA CULTURE

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DATA CULTURE Keynote + Exec Track Birmingham 8th December 2015


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UK Business Lead for BI & Analytics Jon Woodward : Connect & Follow @JLWoodward www.linkedin.com/in/jonathanwoodward #DataCulture #DataCulture


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Data Culture Industry Immersions Community Other Summits Events Events Sept, London 22nd Sept Data Culture Summit – Business 23rd Sept Data Culture Summit - Technical 22nd Sept Data Culture Dinner - Executives Dec, Birmingham 8th Dec Data Culture Summit, Business 9th Dec Data Culture Summit, Technical 8th Dec Data Culture Dinner, Executive March, London 8th Mar Data Culture Summit, Business 9th Mar Data Culture Summit, Technical 8th Mar Data Culture Dinner, Executive May, London 9th May Data Culture Summit, Business 10th May Data Culture Summit, Technical 9th May Data Culture Dinner, Executive Future Decoded, Nov 10-11th, London Data Culture Tracks https://futuredecoded.microsoft.com/ 10th Nov, Futures Data Platform Roundtable 10th Nov, Dashboard in an Hour 10th Nov, Data Culture Panel 10th Nov, Data Culture Dinner Gartner BI Summit , Feb 29th-1st March, London http://www.gartner.com/events/emea/business-intelligence 29th Feb, Data Culture Dinner 6th October, Reading Dashboard in a Day 27th October, Reading Platform Modernisation 20th January, London Dashboard in a Day Platform Modernisation 11th February, Reading Dashboard in a Day Platform Modernisation 21st March, London Dashboard in a Day Platform Modernisation 21st April, Edinburgh Dashboard in a Day Platform Modernisation 11th May, Reading Dashboard in a Day Platform Modernisation 8th June, London Dashboard in a Day Platform Modernisation 10/11th September Cambridge SQL Saturday http://www.sqlsaturday.com/411/eventhome.aspx October SQL Relay http://www.sqlrelay.co.uk/ 7th Nottingham 8th London 12th Reading 13th Bristol 14th Cardiff 15th Birmingham 28th Nov, London Data Culture PowerBI Edition http://www.eventbrite.com/e/data-culture-day-london-power-bi-edition-tickets-18258788528 5th Nov, London IRM Data Science Track http://www.irmuk.co.uk/edbi2015/postworkshops.cfm UK DATA CULTURE EVENTS 26th Nov, London Dashboard in a Day Platform Modernisation #DataCulture Cloud RoadShow, Feb 29th-1st March, London SQLSaturday, Exeter – 11/12 March SQLBits, May SQL Saturday, Edinburgh – 10/11 June


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Data Culture for Marketing Data Culture Summits – Sept/Dec/Mar/May Data Culture for IT Executives Data Platform Modernisation Data Culture for Finance IoT Track Machine Learning and Analytics Track Visualisation and Data Discovery Track Big Data and Data Management Track Day 1 - Business Day Day 2 - Technical Day Dashboard in a Day #DataCulture


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Data Culture 09.00- 09.30 Dave Coplin – Chief Envisioning Officer, Microsoft 09.30 – 10.00 Mike Bugembe – Chief Data Officer, JustGiving Break 10.15 – 12.30 Morning Tracks Lunch 13.30 – 16.30 Dashboard in a Day Continues Close #DataCulture


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Re-inventinG Productivity Dave Coplin Chief Envisioning Officer @dcoplin Empowering the Future of Work


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Boldly Go…


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“Why work isn’t working and what you can do about it.” Previously…


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The Problem of Productivity


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Working Like Victorians


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“How to outsmart the digital deluge” Out Now….


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the Digital Deluge


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Mobile Disruption


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And Yet?


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Work Harder, Not Smarter


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Breaking the Digital Barrier


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Unlocking The data Dividend


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MAKING THE INVISIBLE VISIBLE


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Taking the Systemic View Which is greener?


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Here be Monsters… Source: Henderson, Bobby (2005). "Open Letter To Kansas School Board". Venganza.org. Archived from the original on 2007-04-07.


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Predicting The future


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Technology’s Copernican Shift


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Ambient Intelligence


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Situational Interaction


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Situational Interaction


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The Rise of the machines


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The Power of Machine Learning


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Patterns and Deep Learning "Aoccdrnig to a rseecharer at Cmabrigde Uinervtisy, it deosn't mttaer in waht oredr the ltteers in a wrod are, the olny iprmoatnt tihng is taht the frist and lsat ltteers be at the rghit pclae. The rset can be a toatl mses and you can sitll raed it wouthit porbelm. Tihs is bcuseae the huamn mnid deos not raed ervey lteter by istlef, but the wrod as a wlohe."


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Moving forward


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Create A Data Culture


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Guilt by (Algorithmic) Association? The algorithm made me do it…


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A question of Trust


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Look for Outcomes not process


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Transformative Thinking


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Image copyright: CBS Studios Inc.


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Remember, Computers are useless…


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40


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No good cause should go unfunded


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b 165 Countries 25m Users $3bn Raised 10 Currencies


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The Predictability Discovery and Engagement


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A recommendation engine to suggest content


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Personalisation


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Traditional methods don’t work in this space


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Lots of research and working with academics


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Its about social relationships and networks


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The answer was staring us in the face every day


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We live in a connected world


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People supporting others


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87million nodes


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420million relationships


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We can run calculations over these networks


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So this is what we planned to build 14 years of giving behaviour, online, web traffic, academic research Engaging Machine Learning Social Graph Theory Personal


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To achieve our vision we built an intelligent machine that… Give Care about Engaging content


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Building a real-time graph is hard!


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Secure Flexibility Always up always on Platform as a service


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HDInsight Azure Cloud Services Azure Service Bus Azure Table Storage F# Azure websites (with Auto scaling & Storage Queues)


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Microsoft Azure


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No good cause should go unfunded


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mike.bugembe@justgiving.com mike@CAOtoday.com @mikeBugembe https://uk.linkedin.com/in/mikebugembe


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Jon Woodward – Business Lead – BI & Analytics, MSFT Gary Richardson – Director of Data Engineering, KPMG Data Culture for Executives #DataCulture Microsoft Data Culture - UK


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Data Culture for Execs 10.15 – 10.30 Intro + Welcome 10.30 – 11.00 Benefits of a Data Culture 11.00 – 11.45 The Future is Data Driven 11.45 – 12.15 Enabling Data Culture in your Organisation 12.15 – 12.30 Next Steps Lunch #DataCulture


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UK Business Lead for BI & Analytics Jon Woodward : Connect & Follow @JLWoodward www.linkedin.com/in/jonathanwoodward #DataCulture #DataCulture


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Director of Data Engineering, KPMG Gary Richardson: Connect & Follow @GaryData https://uk.linkedin.com/in/richardsongary #DataCulture


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Introductions


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Jon Woodward – Business Lead – BI & Analytics, MSFT Benefits of Data Culture #DataCulture Microsoft Data Culture - UK


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What differentiates today’s thriving organizations? Data. #DataCulture


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Devices: “Info Workers Will Erase Boundary Between enterprise and Consumer Technologies.” Forrester Research. Aug. 30, 2012 Apps: “Gartner: Predicts 2013: Business Impact of Technology Drives the Futures Application Services Market.” Nov. 21, 2012 Big data: Paraphrased from “The Impact of the Internet of Things on Data Centers.” Gartner Research, Feb. 27, 2014 Cloud: “Prepare For 2020: Transform Your IT Infrastructure And Operations Practice.” Forrester Research. Oct. 24, 2012 Industry transformation accelerating #DataCulture 75 Years to 100M users 2.4 years


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Data…Driving the Experience #DataCulture


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What do these companies have in common? No Cars No Content No Real Estate no Inventory Business model based on Data Culture #DataCulture


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Entering a New Data World Order www.slideshare.net/jonathanwoodward1 Algorithm’s Things Intelligence #DataCulture


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Age of the Algorithm Algorithm’s #DataCulture Predicating next best outcome Finding patterns Uncovering Anomalies Yesterday


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Age of Things Algorithm’s Things #DataCulture 25 billion Connected “things” by 2020 —Gartner $1.7 trillion Market for IoT by 2020 —IDC Today


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Age of Things Algorithm’s Things #DataCulture Create new business models Provide better service and improve customer experiences Respond to changes in the market faster Improve product availability and usage Open new revenue streams


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Age of Intelligence Algorithm’s Intelligence #DataCulture Credit : Tim Bostrum, Predictions – Ray Kurzweil 2010- Supercomputer to emulate human intelligence 2020 – Human intelligence computing available for $1000 2029 – Pass Turing Test 2030 – non-biological computation will surpass capacity of all living human intelligence 2045 – Singularity Tomorrow


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Age of Intelligence Algorithm’s Intelligence #DataCulture Creating Intelligent Applications Creating more personal experiences Connecting Algorithms and Things


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New Data World Order Gartner predicts that by 2017, 20% of all market leaders will lose their number one position to a company founded after the year 2000 because of a lack of data business advantage #DataCulture


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Be more Productive Data Driven organisations are 5% more productive, MIT - Bynjolfssson 2011 5% more productive =


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Data dividend More people New analytics Diverse data UK Economy - Data Dividend Capture a ?53Bn data dividend from data investments by 2017 Speed Source: IDC & Microsoft, April 2014 Employee productivity Operations improvement Product innovations Customer-facing projects #DataCulture


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#DataCulture How will YOU differentiate YOUR organization?


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Gary Richardson – Director of Data Engineering, KPMG The Future is Data Driven #DataCulture Microsoft Data Culture - UK


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Data Culture : Disrupting with data Gary Richardson, UK Head of Data Engineering KPMG


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Disruptor or disrupted?


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Key concepts that are driving data innovation Schema on read Open API’s Cloud Scale Model Portability Automation


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Increasing the return from data value chain Data Processing Data Collection Data Science Predict Action Value Creation Value Protection Collect everything Process on demand Look for opportunities Making Predictions


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Discover patterns in data streaming automatically from remote sensors and machines Research logs to diagnose process failures and prevent security breaches Understand how your customers feel about your brand and products – right now Analyze location-based data to manage operations where they occur Understand patterns in files across millions of web pages, emails, and documents Geographic Unstructured Server Logs Sentiment Sensors Platforms New Data types Leveraging new types of data Only by leveraging new types of data both internal and external can real value of analytics be unlocked


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Traditional Organisations = Legacy, change is needed Schema on read Open API’s Cloud Model Portability Automation Streaming Data Getting the data in Applying the machine


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High level data science workflow feature selection and scoring Product Search Observable Event Product Recommendation Feature Selection Process Recommendation Take Action Machine Learning Platform Score Features using Algorithms for the Event


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Use in Production Score in real-time the decision for which the model was trained Primary data manipulation and management Model build pipeline process Observable set of data that needed to be passed down the pipeline Select Feature Feature Transformation Train the model Train, validate, adjust, relearn, set curriculum of the model Publish API Publish the API to enable model to be utilised Monitor and Evaluate Continuous monitoring of model performance Re-train model


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GLM K-Means Neural Networks Platforms Algorithms SVM Naive Bayes Recommenders Cox Prop Hazards Random Forests PCA Common algorithms


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Where are the opportunities for you? Data Science Insight Backed Products Data Marketplaces Big Compute Platforms


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Being creative with data even with the humble help desk call Platforms Contagion Risk 9.1 million service calls processed from start to finish in less than 4 hours 130 billion connected events identifying likely to cause of Contagion Graph Analysis Unstructured Data Processing


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Increasing Data Culture = Increases the Data Dividend


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The information contained herein is of a general nature and is not intended to address the circumstances of any particular individual or entity. Although we endeavour to provide accurate and timely information, there can be no guarantee that such information is accurate as of the date it is received or that it will continue to be accurate in the future. No one should act on such information without appropriate professional advice after a thorough examination of the particular situation. Gary Richardson Director, UK Head of Data engineering KPMG in the UK T: +44 20 7311 4019 E: gary.richardson@kpmg.co.uk Twitter: @garydata


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Jon Woodward – Business Lead – BI & Analytics, MSFT Enabling Data Culture #DataCulture Microsoft Data Culture - UK


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Lead from the top Put someone in control (CIO, CDO, CAO) Emphasise data quality and governance Treat data the same as money Culture to collaborate, open, inclusive


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Lead from the top Put someone in control (CIO, CDO, CAO) Emphasise data quality and governance Treat data the same as money Culture to collaborate, open, inclusive


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Lead from the top Put someone in control (CIO, CDO, CAO) Emphasise data quality and governance Treat data the same as money Culture to collaborate, open, inclusive


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Lead from the top Put someone in control (CIO, CDO, CAO) Emphasise data quality and governance Treat data the same as money Culture to collaborate, open, inclusive


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Lead from the top Put someone in control (CIO, CDO, CAO) Emphasise data quality and governance Treat data the same as money Culture to collaborate, open, inclusive


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Refine structure and roles Educate entire organisation Be transparent Reinforce data driven behaviours Build the use into every aspect


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Refine structure and roles Educate entire organisation Be transparent Reinforce data driven behaviours Build the use into every aspect


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Refine structure and roles Educate entire organisation Be transparent Reinforce data driven behaviours Build the use into every aspect


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Refine structure and roles Educate entire organisation Be transparent Reinforce data driven behaviours Build the use into every aspect


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Refine structure and roles Educate entire organisation Be transparent Reinforce data driven behaviours Build the use into every aspect


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Metrics, scorecard, leading indicators Real-time dashboards Start with the data Review & question to drive requirement for new data Look for areas to automate


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Metrics, scorecard, leading indicators Real-time dashboards Start with the data Review & question to drive requirement for new data Look for areas to automate


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Metrics, scorecard, leading indicators Real-time dashboards Start with the data Review & question to drive requirement for new data Look for areas to automate


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Metrics, scorecard, leading indicators Real-time dashboards Start with the data Review & question to drive requirement for new data Look for areas to automate


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Metrics, scorecard, leading indicators Real-time dashboards Start with the data Review & question to drive requirement for new data Look for areas to automate


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Build versions of the truth Enable sharing and exploration Expand the data footprint Move beyond big data to all data Leverage the edge


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Build versions of the truth Enable sharing and exploration Expand the data footprint Move beyond big data to all data Leverage the edge


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Build versions of the truth Enable sharing and exploration Expand the data footprint Move beyond big data to all data Leverage the edge


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Build versions of the truth Enable sharing and exploration Expand the data footprint Move beyond big data to all data Leverage the edge


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Driving a Data Culture Leadership Decision Making Organisation Data #DataCulture Build versions of the truth Enable sharing and exploration Expand the data footprint Move beyond big data to all data Leverage the edge


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What has worked in driving a Data Culture? #DataCulture


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128 What does the future look like ? All Data + All Things Machine + Intelligence Human + #DataCulture


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129 Where to Look to get started Agent allocation Warehouse efficiency Smart buildings Predictive maintenance Supply chain optimization User segmentation Personalized offers Product recommendation Fraud detection Credit risk management Sales forecasting Demand forecasting Sales lead scoring Marketing mix optimization EXAMPLE SOLUTIONS Sales and marketing Finance and risk Customer and channel Operations and workforce #DataCulture


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130 Example GiveGraph www.justgiving.com 81 Million nodes 361 Million Relationships #DataCulture


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Gary Richardson – Director of Data Engineering, KPMG Building a Data Science Capability #DataCulture Microsoft Data Culture - UK


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Building the DS&E team to maximise the data dividend


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Structuring the team for success Data Science Data Engineering DevOps Machine Learning Deep Learning Brittle Models Industrialization Software Development Data Pipelines Cluster Management Cloud Orchestration Automation


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Head of Data Science Data Scientists Lead Data Scientist Data Engineers Senior Data Engineer DevOps Lead DevOps Data Science Data Engineering DevOps Product Management & Project Management Graduates Organization Structure


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Ways of Working Confluence Jira Stash Bamboo Describe the outcome Delegate the work Control the code Automate the deployment


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Jon Woodward – Business Lead, BI & Analytics, MSFT Next Actions #DataCulture Microsoft Data Culture - UK


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Leverage the Edge Tune your business to embrace Machine Intelligence 138 What Should we do Today Build a Data Culture Plan Move beyond Big Data #DataCulture


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