Long-Term Outcomes: Customer-Centered Product Strategy For Machine Intelligence - Flying Blind Part

Long-Term Outcomes: Customer-Centered Product Strategy For Machine Intelligence - Flying Blind Part

• 1. LONG TERM OUTCOMES CUSTOMER-CENTERED PRODUCT STRATEGY FOR MACHINE INTELLIGENCE

• 2. JOE LAMANTIA Currently: Available > call me / hire me! Previous: Amazon, SallieMae, Bottomline, Capital One, Paypal, Oracle, Endeca Focus: Product & Design leadership, Strategy for emerging tech joe.lamantia@gmail.com joelamantia.org https://www.youtube.com/joelamantia https://www.slideshare.net/moJoe/presentations https://www.linkedin.com/in/digitaljoelamantia/

• 3. Flying Blind On A Rocket Cycle: Case Study on Customer-centered Product Strategy for Machine Intelligence This session shares a case study on the growth and evolution of B2B product portfolios driven by machine intelligence for a leading SaaS product maker. This case study reviews a series of new product efforts; outlines the methods, tools, and practices that powered product discovery and strategic planning; traces the evolution of product portfolios; and considers business outcomes from building and growing a portfolio of new analytics products and services for Oracle. ▸ Craft customer-centered product strategies ▸ Build and evolve customer-centered products and portfolios ▸ Establish effective, innovative, customer-centered product strategy capabilities and practices

• 4. LONG TERM OUTCOMES MACHINE INTELLIGENCE PRODUCTS AND SERVICES

• 5. =

• 6. ANALYTICS PRODUCTS EMERGING SPACES

• 7. "PRODUCT STRATEGY CHARTS THE COURSE OF PRODUCT INVESTMENT AND EVOLUTION" Joe Lamantia DEFINITION

• 8. EMERGING SPACES NEW PRODUCTS ANALYTICS PRODUCT STRATEGY $$$

• 9. WHY ARE YOU HERE? WHERE ARE YOU GOING?

• 10. 1. GET IN THE HEADS OF DATA SCIENTISTS 2. BE THE SPIRIT OF THE PRODUCT

• 11. HOW WILL YOU GET THERE?

• 12. CONTINUOUS LEARNING & LEAN STRATEGY HYPOTHESIS > 1-2 WK SPRINT >> OUTCOME

• 13. SPIRIT OF THE PRODUCT: DATA SCIENTISTS:

• 14. PRODUCT LANDSCAPE: VALUE CHAIN:

• 15. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal Requires a Fundamentally New Approach 15 A single intuitive, interactive and visual user interface Explore Discover Transform Find for anyone to quickly find, explore, transform and analyze data in Hadoop then share results for enterprise leverage New role >> New product category

• 16. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal • Understand shape of the data. Visualize attributes by type • Entropy based sorting by information potential • View attribute statistics, data quality and outliers • Use scratch pad to see statistical correlations between attribute combinations • Evaluate whether a data set is worthy of further investment 16 Explore the Data and Understand Potential

• 17. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal 17 Oracle Big Data Discovery. The Visual Face of Hadoop Explore Discover Transform Find

• 18. OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING A SERIES OF INVESTMENTS

• 19. OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING CYCLE TIME ~14 months

• 20. CLARITY SPEED TIMING MOMENTUM IMPACT =

• 21. OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING A SERIES OF INVESTMENTS

• 22. Chapter 5 What's New and Changed in this Release This section describes the changes made for this release of BDD, including new, deprecated, and unsupported features. New and updated features Data set settings controlled by edp-cli.properties or in Studio New and updated features The following features have been added, improved, or updated for the Oracle Big Data Discovery 1.4.x release. Transform-related features This release includes these transform-related features and improvements: • You can use a new Get Sentiment transformation in Studio to extract positive or negative sentiment from attributes in your data, or label some attributes as having a positive or negative sentiment. Improvements in data scale and management This release includes these improvements to data and scale management: • Continued data ingest parallelization further improves performance for data loading. • The Data Processing component of BDD uses Parquet format for its sample files, instead of the Avro format used in the previous releases. During an upgrade to this release, Avro files are converted to Parquet. Parquet is an efficient storage format natively supported in Hive that separates storing data from metadata and improves query performance for columnar-based data in analytics applications. BDD as a complete toolkit in your data lab This release includes these changes: • As the BDD administrator, you can better manage job status for data processing jobs in BDD. You can use new command line flags to get the job status, list currently running jobs, and cancel jobs by job ID. • The stability and robustness of the indexing process in BDD has been improved: the Dgraph process validates all of its provided command line options and ports, reports inconsistencies, uses defaults in cases when invalid values are specified, and exits with errors in cases of port conflicts. • The Workflow Manager Service is added in this release. Studio and the DP CLI use the Workflow Manager Service to run several data processing workflows in BDD. You can control the Workflow Manager Service settings in the edp.properties file in $BDD_HOME/workflowmanager/dp/config. This file is also new in this release. The introduction of the Workflow Manager Service separates the frontOracle® Big Data Discovery : Getting Started Guide Version 1.4.0 • October 2016 OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING CYCLE TIME ~6 months

• 23. OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING CYCLE TIME ~12 weeks X

• 24. OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING CYCLE TIME * + 2 years to prioritize… ~4 weeks

• 25. CLARITY SPEED TIMING MOMENTUM IMPACT =

• 26. CUSTOMERS

• 27. PRODUCT 6 releases portfolio consolidation

• 28. PRODUCT 6 releases portfolio consolidation designs an ideal course the return voyage

• 29. EVOLUTION “Long view = tools in this segment could ‘eat’ BI marketshare by adding reporting and other structured analytical capabilities that capture customers who do not have large BI stacks now, begin investing here, and subsequently need BI capability.”

• 30. SAME DESTINATION EVOLVING COURSE

• 31. PORTFOLIO New capabilities Expanded portfolio

• 32. OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING CYCLE TIME Chapter 5 What's New and Changed in this Release This section describes the changes made for this release of BDD, including new, deprecated, and unsupported features. New and updated features Data set settings controlled by edp-cli.properties or in Studio New and updated features The following features have been added, improved, or updated for the Oracle Big Data Discovery 1.4.x release. Transform-related features This release includes these transform-related features and improvements: • You can use a new Get Sentiment transformation in Studio to extract positive or negative sentiment from attributes in your data, or label some attributes as having a positive or negative sentiment. Improvements in data scale and management This release includes these improvements to data and scale management: • Continued data ingest parallelization further improves performance for data loading. • The Data Processing component of BDD uses Parquet format for its sample files, instead of the Avro format used in the previous releases. During an upgrade to this release, Avro files are converted to Parquet. Parquet is an efficient storage format natively supported in Hive that separates storing data from metadata and improves query performance for columnar-based data in analytics applications. BDD as a complete toolkit in your data lab This release includes these changes: • As the BDD administrator, you can better manage job status for data processing jobs in BDD. You can use new command line flags to get the job status, list currently running jobs, and cancel jobs by job ID. • The stability and robustness of the indexing process in BDD has been improved: the Dgraph process validates all of its provided command line options and ports, reports inconsistencies, uses defaults in cases when invalid values are specified, and exits with errors in cases of port conflicts. • The Workflow Manager Service is added in this release. Studio and the DP CLI use the Workflow Manager Service to run several data processing workflows in BDD. You can control the Workflow Manager Service settings in the edp.properties file in $BDD_HOME/workflowmanager/dp/config. This file is also new in this release. The introduction of the Workflow Manager Service separates the frontOracle® Big Data Discovery : Getting Started Guide Version 1.4.0 • October 2016 ~5 years

• 33. BUSINESS STRATEGY: ANALYTICS PRODUCTS FOR EMERGING SPACES

• 34. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Joe Lamantia | Product Strategist: Oracle Endeca Big Data Discovery 34

• 35. ANALYTICS PRODUCTS EMERGING SPACES

• 36. Chapter 5 What's New and Changed in this Release This section describes the changes made for this release of BDD, including new, deprecated, and unsupported features. New and updated features Data set settings controlled by edp-cli.properties or in Studio New and updated features The following features have been added, improved, or updated for the Oracle Big Data Discovery 1.4.x release. Transform-related features This release includes these transform-related features and improvements: • You can use a new Get Sentiment transformation in Studio to extract positive or negative sentiment from attributes in your data, or label some attributes as having a positive or negative sentiment. Improvements in data scale and management This release includes these improvements to data and scale management: • Continued data ingest parallelization further improves performance for data loading. • The Data Processing component of BDD uses Parquet format for its sample files, instead of the Avro format used in the previous releases. During an upgrade to this release, Avro files are converted to Parquet. Parquet is an efficient storage format natively supported in Hive that separates storing data from metadata and improves query performance for columnar-based data in analytics applications. BDD as a complete toolkit in your data lab This release includes these changes: • As the BDD administrator, you can better manage job status for data processing jobs in BDD. You can use new command line flags to get the job status, list currently running jobs, and cancel jobs by job ID. • The stability and robustness of the indexing process in BDD has been improved: the Dgraph process validates all of its provided command line options and ports, reports inconsistencies, uses defaults in cases when invalid values are specified, and exits with errors in cases of port conflicts. • The Workflow Manager Service is added in this release. Studio and the DP CLI use the Workflow Manager Service to run several data processing workflows in BDD. You can control the Workflow Manager Service settings in the edp.properties file in $BDD_HOME/workflowmanager/dp/config. This file is also new in this release. The introduction of the Workflow Manager Service separates the frontOracle® Big Data Discovery : Getting Started Guide Version 1.4.0 • October 2016 ANALYTICS PRODUCTS EMERGING SPACES

• 37. WHY ARE YOU HERE? WHERE ARE YOU GOING? HOW WILL YOU GET THERE? ANALYTICS PRODUCTS EMERGING SPACES NEW PRODUCTS EXPANDED PORTFOLIO

• 38. NEW PRODUCTS NEW SERVICES NEW CATEGORIES NEW CUSTOMERS NEW CAPABILITIES NEW TECHNOLOGY ANALYTICS PRODUCTS EMERGING SPACES

• 39. ANALYTICS PRODUCTS EMERGING SPACES

• 40. OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING A SERIES OF INVESTMENTS

• 41. next generation secret project 200 person organization legacy offerings whole new product new category & platform vision napkin plan first-mover CIOs end-to-end new technology conventional wisdom

• 42. next generation secret project 200 person organization legacy offerings whole new product new category & platform ANALYTICS PRODUCTS EMERGING SPACES vision napkin plan first-mover CIOs end-to-end new technology conventional wisdom

• 43. NEW CATEGORY 43

• 44. “Platfora is an Hadoop-only, big data discovery platform that includes data preparation and visualisation. Its goal is to empower business users to blend, transform and integrate data sets to, as part of exploratory analyses which produce stunning visualisations on PBs of data. Yes, that 's a P. It 's neither an ETL tool nor an advanced analytics tool and does not pretend to be either, although future releases had alluded to non-Hadoop data source integration and machine learning capabilities. Think of Platfora as a combination of superb tools like Trifacta and ZoomData. Platfora 's value proposition can be summarised in a simple sketch comparing the old-world vs new world approach to data engineering for insight.” https://www.kainos.com/insights/news/why-workdays-acquisition-of-platfora-makes-sense CATEGORY EVOLUTION

• 45. “Platfora is an Hadoop-only, big data discovery platform that includes data preparation and visualisation. Its goal is to empower business users to blend, transform and integrate data sets to, as part of exploratory analyses which produce stunning visualisations on PBs of data. Yes, that 's a P. It 's neither an ETL tool nor an advanced analytics tool and does not pretend to be either, although future releases had alluded to non-Hadoop data source integration and machine learning capabilities. Think of Platfora as a combination of superb tools like Trifacta and ZoomData. Platfora 's value proposition can be summarised in a simple sketch comparing the old-world vs new world approach to data engineering for insight.” https://www.kainos.com/insights/news/why-workdays-acquisition-of-platfora-makes-sense CATEGORY EVOLUTION

• 46. OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING CYCLE TIME ~5 years

• 47. OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING

• 48. DATAMEER ANNOUNCES $40M INVESTMENT AS IT PIVOTS AWAY FROM HADOOP ROOTS “It’s never easy pivoting like this, but the investors are likely hoping that the company can build on its existing customer base, while taking advantage of the market need for data science processing tools. Time will tell if it works.” https://techcrunch.com/2019/10/29/datameer-announces-40m-investment-as-it-pivots-away-from-hadoop-roots/ + =

• 49. OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING CYCLE TIME ~5 years

• 50. OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING

• 51. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Joe Lamantia | Product Strategist: Oracle Endeca Big Data Discovery 51 Featurize Wrangle Visual Analysis Interactive Queries Data Discovery Modeling Application Acquire Ingest & Clean Manage & Update Model Train Update Evaluate Build Train Deploy Store & Monitor Expose Discovery Workbenches BDD (now) ML services Oracle Machine Learning Discovery & Modeling Platform BDD & ML (combined analysis offering ?) New Category $$$$

• 52. OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING CYCLE TIME ~8 years

• 53. ANALYTICS PRODUCTS EMERGING SPACES

• 54. ANALYTICS PRODUCTS EMERGING SPACES $4 BILLION

• 55. PRODUCT STRATEGY $43B EMERGING SPACES NEW PRODUCTS ANALYTICS

• 56. CLARITY SPEED TIMING MOMENTUM IMPACT =

• 57. OPPORTUNITY ASSESSMENT PRODUCT INVESTMENT PRODUCT DISCOVERY PRODUCT & PORTFOLIO PLANNING CYCLE TIME ~12 years

• 58.

• 59.

• 60. THANK YOU! CALL ME… joe.lamantia@gmail.com joelamantia.org https://www.youtube.com/joelamantia https://www.slideshare.net/moJoe/presentations https://www.linkedin.com/in/digitaljoelamantia/