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Self-Service Analytics Framework - Connected Brains 2018

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LoQutus helps organisations to innovate with analytics and to get insights with data visualisation. We also build large scale data layers to enable interaction with core data, and develop data-driven applications to deliver the insights our customers need. During this session we’ll share what we have learned along the way. We’ll show you our framework for self-service analytics & insights, and some successful case studies.

Published in: Data & Analytics
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Self-Service Analytics Framework - Connected Brains 2018

  1. 1. Supported by: A framework for Self-Service Analytics & Insights Connected Brains 2018
  2. 2. We speak your language Supported by:
  3. 3. Introduction – meet the ‘brains’ Education Engineer’s degree, Civil Engineer in Electromechanics Professional experience KBC Group: 2006-2014 LoQutus : 2014 – current Certification Data Science, John Hopkins University Archimate 2.0 Thomas Michem Information Architect Lead strategist Analytics & Insights Thomas.michem@loqutus.com @michemt
  4. 4. What can you expect Intro Why we do what we do Framework for Self-Service Analytics & Insights Conclusions & KeyTake-aways
  5. 5. Information Reality
  6. 6. What to do with these trends? https://www.linkedin.com/pulse/why-trends-you-ride-biggest-choices-strategy-chris-bradley/
  7. 7. Analytics Use Cases Increased Customer Service New revenue possibilities Operational EfficiencyCompetitive Advantage
  8. 8. 10 The Information Value Chain Data & Context Information Knowledge Actions Goals Analytics to make complex information simple. Insights to make your experts even better at what they do.
  9. 9. What makes data complex?
  10. 10. Information Filters DASHBOARD If you want to prevent data splattering everywhere, put a dashboard in front of it!
  11. 11. Healthcare Analytics
  12. 12. City Distribution Monitoring
  13. 13. What can you expect Intro Why we do what we do Framework for Self-Service Analytics & Insights Conclusions & KeyTake-aways
  14. 14. What’s your data menu? It’s about options Data is not always about oil refineries.
  15. 15. Information Lifecycle Ingest Analyze Prepare Store Use
  16. 16. Self-Service Appetite Ingest Store Prepare Analyse Use Ingest Store Prepare Analyse Use Ingest Store Prepare Analyse Use Ingest Store Prepare Analyse Use Ingest Store Prepare Analyse Use Data Guru Data DrivenData MindedData SkilledData Chef
  17. 17. It’s about empowerment
  18. 18. Self-service leads to more analytics output
  19. 19. Self-Service also means not being afraid of end-user tooling preferences
  20. 20. Excel Optimisation Levels Excel core arithmetic Advanced Excel, vlookups, pivots PowerPivot / PowerQuery / DAX Optimised data layer + PowerPivot Capabilities Expertise 1 mio rows 10+ mio rows > 1 billion rows
  21. 21. Managing Self-Service Self-ServiceManaged Solutions
  22. 22. Why use a framework? A framework's power is 10% technical, & 90% organizational. It focuses your team by removing questions they'd spend time disagreeing on. Why What How do we deliver Analytics & Insights
  23. 23. Strategy & Governance Architecture Methodology Data Products LoQutus Analytics Framework What is the structure that enables analytics? Important is to consider both the information architecture (business oriented) and the data architecture (technology oriented) What do your analytics efforts deliver? What are the outputs, outcomes and value? An iterative approach for data projects, describing data, to communicate & assess quality Execution Enablement Setting the scene. How to build a vision, approach, get people involved and define roles & responsibilities.
  24. 24. Strategy & Governance Architecture Methodology Data Products LoQutus Analytics Framework Execution Enablement
  25. 25. Information Strategy Business becoming data-driven Information as an asset IT leveraging technology for Modern Data Architecture Providing engineered solutions
  26. 26. Information Governance Owned Described Quality – Fit for purpose Access (Security & Privacy) & Use Governance How are we going to get there? Where are we going? What is Information Governance? Proactively managing your information, to support your business to achieve it’s strategy and vision The Data Governance Coach - Nicola Askham
  27. 27. Walk before you run... but include interval training Descriptive Analytics Diagnostic Analytics Predictive Analytics Prescriptive Analytics Difficulty Value Hackathons Ideation Experiment Prototype Vision
  28. 28. Rockstar Data Scientists
  29. 29. DataTeam Ingest Analyze Prepare Store Use Data Engineers Business Analist Data Analysts Data Architect Data Scientist CxO Data Stewards Business Expert Data Owner Data Leaders
  30. 30. Strategy & Governance Architecture Methodology Data Products LoQutus Analytics Framework Execution Enablement
  31. 31. ©LoQutus 34 People can’t share knowledge If they don’t speak a common language. IA Content DataModel Meta Data
  32. 32. Mapping your Information Architecture Sales Organization Structure Projects Products Services Assets Customer Market Suppliers Applications Inventory Deliveries Shop Segment Value Touch Points Planning RoutesMaterials Loyalty Countries Invoices Margin Processes Infra structure People Buildings Prospects Orders Integrations Questions Budgets
  33. 33. Information Architecture Office Modelling Catalogue tool
  34. 34. The full Data Hierarchy Analytical Data Master Data Reference & Metadata Transactional Data Streaming Data ANALYTICAL DATA KPI’s,Aggregated data, enriched data MASTER DATA Clients, Products, Enterprise Structure, .. REFERENCE & META DATA Classification schemas, external data and data about data TRANSACTIONAL DATA Records describing key agreements with your customers STREAMING DATA All measureable interactions with clients, employees and assets
  35. 35. Data Lake or DataWarehouse?
  36. 36. Data Quality You cannot inspect quality into a product. The quality is there or it isn't by the time it's inspected. Information Quality is the degree to which information can be a trusted source for every of it’s required uses. In other words, the quality indicates if the information is fit for purpose. Operational Analytical
  37. 37. TIDY DATA “The reality is, data scientists spend from 50 to 80 percent of their time wrangling big data—collecting and preparing unruly data sets before they’re ready for business use. ” http://www.nytimes.com/2014/08/18/technology/for-big-data-scientists-hurdle-to-insights-is-janitor-work.html
  38. 38. Strategy & Governance Architecture Methodology Data Products LoQutus Analytics Framework Execution Enablement
  39. 39. LoQutus Analytics & Insights Kickstarting Analytics Choosing the right way to guide your analytics journey Discover Quick-scan of your potential value in analytics, your core data assets, and the key hurdles that lock your data. Kickstart Do you have a data challenge but don’t know where to start? We’ll kickstart your analytics endeavors! Foundation The right environment for asking questions to all your data assets, and getting timely results. BusinessValue Information Architecture Data Understanding Data Exploration Data Architecture DataWarehouse Data Pipelines Data Lake Data Preparation Prototyping Dashboards Machine Learning
  40. 40. LoQutus Analytics & Insights KICKSTART FOUNDATION Pilot Rollout Data Governance Data Architecture Data Map Understanding DISCOVERY Kickoff & Inspiration BUSINESS VALUE Pilot Ideation Business & Technology Roadmap Analytics Use Cases Pilot Tracks Insights Delivery Prototyping Training & Self-service Data Engineering
  41. 41. Model Building Expert Evaluation Data Understanding Business Understanding Data Preparation Deliver Insights 01 02 03 0405 06Better Business Questions Data Model ETL / Feature Engineering Model Selection and Evaluation Feedback with stakeholders Deploy, Publish, Share Qrisp BI Based on CRISP-DM Cross-Industry Standard for Data Mining
  42. 42. Strategy & Governance Architecture Methodology Data Products LoQutus Analytics Framework Execution Enablement
  43. 43. Data Products DataVisuals Visualising data for analysis Basic Reports & Queries Getting an overview of facts or events Dashboards Key views on data, visualizing KPI’s, evolution and patterns Analytic Models Advanced analytics automating decisons, pattern recognition, recommendations, … Interactive Exploration tools Environment to interactively query and visualize data Data Notebooks Step by step reproducible analysis of data sets through a combination of text and visuals.
  44. 44. AnalyticsValue Chain WHAT HAPPENED? Descriptive Analytics WHY DID IT HAPPEN? Diagnostic Analytics WHAT WILL HAPPEN? Predictive Analytics HOW CAN WE MAKE IT HAPPEN? Prescriptive Analytics Data Notebooks Dashboards Reports Visuals Analytic Models
  45. 45. Explore before Advanced Analytics Visual Analytics Advanced Analytics Start with Visual Analytics Optimize with Advanced Analytics
  46. 46. People are visual
  47. 47. First step in Analytics? Make your data visual!
  48. 48. Tooling http://www.loqutus.com/content/dashboarding-not-tool
  49. 49. Explore before Advanced Analytics Visual Analytics Advanced Analytics Start with Visual Analytics Optimize with Advanced Analytics
  50. 50. A HelicopterView on Analytics Data Science Artificial Intelligence Machine Learning Deep Learning Deep Learning algorithms attempt to mimic the activity of layer of neutrons in the human brain. Multilayered Neural Networks Live Speech translation,AlphaGO, Watson, Not Deep Blue (chess) Machine Learning covers algorithms that learn from data (supervised learning = from examples, unsupervised learning = finding patterns) Artificial Intelligence A program that can sense, reason, act, and adapt Data Science is everything, including Data Preparation (a.k.a. ‘The HardWork’)
  51. 51. Machine Learning Applications
  52. 52. What can you expect Intro Why we do what we do Framework for Self-Service Analytics & Insights Conclusions & KeyTake-aways
  53. 53. DATA Matters
  54. 54. Know your DATA
  55. 55. Improve with DATA
  56. 56. Self-Service Analytics Bigger Brains OR Connected Brains
  57. 57. Start your analytics journey Discover Quick-scan of your potential value in analytics, your core data assets, and the key hurdles that lock your data. Kickstart Do you have a data challenge but don’t know where to start? We’ll kickstart your analytics endeavors! Foundation The right environment for asking questions to all your data assets, and getting timely results. BusinessValue Information Architecture Data Understanding Data Exploration Data Architecture DataWarehouse Data Pipelines Data Lake Data Preparation Prototyping Dashboards Machine Learning

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