Surfing Technology Waves

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Information about Surfing Technology Waves

Published on June 11, 2016

Author: idigdata


1. Jen Underwood Founder & Principal Consultant @idigdata Surfing Technology Waves

2. Jen Underwood 20 years of industry experience Former Microsoft BI & Analytics Technical Product Manager and “hands-on” implementer Bachelor of Business Administration – Univ. of Wisconsin Milwaukee Post Grad Certificate Computer Science – Data Mining Univ. of California, San Diego About the Speaker @idigdata

3. Surfing Technology Waves Transformational trends Job and career trends Blue ocean opportunities New world of data Agenda

4. Why? Beyond hype, it is imperative to understand when to embrace a technology trend in its formative stages.

5. “Decision making and the techniques and technologies to support and automate it will be the next competitive battleground for organizations. Those who are using business rules, data mining, analytics and optimization today are the shock troops of this next wave of business innovation.” - Tom Davenport, Competing on Analytics

6. Digital business transformation Cloud computing Intelligent analytics Smart machines Internet of things Physical + virtual world Top Technology Trends

7. Transformational Trends

8. Explore digital business models or be disrupted Innovate through the business ecosystem Intelligent big data and predictive analytics Become an experimental organization Huge “Blue Ocean” Opportunity

9. March 2015 Smart Phone vs. Computer Usage Source:

10. Blending Physical and Virtual Worlds

11. Blending Physical and Virtual Worlds

12. Maximize existing resources “UBER” Sharing Economy Knowledge, Content and Talent-Sharing Analytics marketplaces Crowdfunding with Kickstarter and Indiegogo Virtual Assistants, Elance, and TaskRabbit

13. BLS 2010 Occupations Source: Oxford Martin School

14. Will your job be done by a machine?

15. Economic crash excessive analytics demand to navigate unplanned business scenarios

16. Connections to cloud-hosted data have increased by 28% in the past 15 months. By the first quarter of 2016, 70% of all connections were hosted in the cloud. Databases provided as a service, like Amazon Redshift and Google BigQuery, are gaining market share. In two years, they have grown by 125% and today represent 28% of all connections. Tableau Data Sources Research Source: Tableau cloud-data-brief-where-does-your-data-live-54617

17. Source: Tableau

18. Source: Tableau Source: Tableau

19. Source: Tableau

20. Information explosion, new insights 90% of the world’s data has been created over the last two years alone1 Shift to cheaper, faster computing, on demand 45% of total IT spend will be cloud-related by 20202 Faster data-savvy decisions than competitors 5X Companies that use analytics are 5x more likely to make decisions faster than competitors3 Transformative opportunity 1. IDC. 2. Josh Waldo Senior Director, Cloud Partner Strategy, Microsoft. 3. Bain & Company, The Value of Big Data: How Analytics Differentiates Winners, 2013.

21. Data is GOLD Make data accessible Choice & open standards Scale storage and processing Secure and compliant Simple to use Everyone Needs to Master Data

22. 3D and immersive data experiences Analytics automation and embedding Natural language and cognitive systems Predictive and prescriptive analytics Real-time and streaming analytics Big Data, IoT and data lakes Cloud and hybrid data integration Growing Analytics Trends Today

23. Vendors Unity 3D, Oculus Rift, Hololens, WebGL, Google, and more Discover and understand patterns hidden in data Scientific, health, game apps early adoption; now expanding into other areas Immersive Data Experiences Source:

24. Unity 3D - 3-D data browser is just one tool Caltech visualization-to-life/ IVIZ - Immersive Experiences

25. Vendors Microsoft, Oracle Endeca, DataRPM, Thoughtspot, Zoomdata and more Queries via search and speech Index data, not model Natural Language Query Source: Gigaom language-business-intelligence/

26. Vendors Narrative Science, Automated Insights, and more Basic descriptions of the charts Intelligent descriptions in more advanced solutions Natural Language Reports

27. Moving Beyond Descriptive What happened? Why did it happen? What is happening? What will happen? Competitive Advantage Business Impact Descriptive Analytics Diagnostic Analytics Predictive Analytics Prescriptive Analytics I didn’t know I need to know I didn’t know I want to know I know I want to know I know I need to know

28. Vendors IBM Watson, BeyondCore, SAP (formerly KXEN), Data Robot and more Citizen Data Science Automation of descriptive and CRISP-DM processes Automated Analytics 4 2 IBM Watson

29. SAP Predictive Analytics

30. BeyondCore

31. Vendors WhereScape, Kalido, Ajilius, Attunity, TimeXtender and more Historically slow and expensive High failure rates Today automated and prepackaged solutions Automating Data Warehouse Builds

32. Vendors SAS, IBM, Microsoft, Knime, RapidMiner, Dell and more Data mining, machine learning, and forecasting More Open Source, R, Python Predictive Analytics

33. Vendors Frontline Systems, Oracle, SAS, IBM and more What-If, Simulation and Optimization Combines historical data, business rules, mathematical models, variables, constraints and machine learning algorithms. How can we achieve the best outcome and address uncertainty? Simulations run with known and randomized variables to recommend next steps, display scenarios and see range of possible outcomes. Prescriptive Analytics

34. Frontline Systems

35. Dynamic learning: gets smarter each interaction Natural language processing to understand complexities of unstructured data Hypothesis generation and evaluation by applying advanced analytics to weigh and evaluate a panel of responses Language, text, image, emotion and more Capability to analyze and understand human communications at scale Cognitive Computing 5 2

36. IBM Watson

37. False tweet wiped $136 billion from S&P 500 in 2 minutes Real-Time and Streaming Analytics

38. Modern Architecture Hadoop/Data Lake complements a data warehouse Big Data, IoT and Data Lakes

39. Vendors Almost everyone! Data gravity dictates need to move data for hybrid connectivity Cloud and Hybrid BI Forrester Cloud BI Wave Q4 2015

40. Source: Dave McCrory Principles of data gravity

41. Speed of light decisions Even with fast networks and caching, distance, bandwidth and latency = HUGE challenges Timely querying from a BI app with a global data center footprint vastly improves BI user experience Need to defy data gravity Where is your data in the cloud?

42. Escalating complexity Historical bulk/batch data movement data integration no longer appropriate, can’t copy and move all the data or wait for a long time for it Self-service BI demand for data is growing Integration and information governance becoming are critical long-term success factors for IT and analytics leaders – seeing new roles such as CDO Data everywhere

43. Combination of data delivery styles Bulk/batch data movement Data federation/virtualization Message-oriented movement Data replication and synchronization Data integration tools

44. Data as a Service Time-to-solution is 5-10x faster than traditional ETL techniques Less costly compared to data replication and consolidation IT creates views aka data services Business reports connect and transparently query hybrid data Data virtualization for agility

45. Hybrid Data Integration

46. Denodo Unified view of data Virtual entities designed for use in reporting apps Saved Queries Catalog Search

47. Cisco Information Server

48. Enterprise Data Catalogs Knowledge on meaning, structure, location and usage of data across the enterprise Data source directory containing metadata regardless of data source type or location Integration with BI Tools Find data stored anywhere

49. Enjoy the waves of change in analytics Keep a pulse on transformational trends Monitor top job and career changes on Indeed, professional groups, vendor messaging and other sites Reinvent yourself or your business in the new world of data Grab your surfboard 7 2


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