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Greenfield Data
Platform Implementation
Enabling Data Science on Azure
IPPON 2019
Data Practice Lead at Ippon
Technologies, a boutique
consulting firm specializing in
Data, Cloud, DevOps, and
Application Development.
Ippon has deep expertise across
all major cloud platforms: AWS,
Azure, and GCP.
Nearly 20 years of data
consulting experience across
multiple industries, including
Financial Services, Health and
Life Sciences, and Media
Previous clients include
Morgan Stanley, FINRA,
Warner Music, and McDonald's
Corporation
Patent Pending: Data Quality
Analysis Tool
Peter Choe
U.S. Data Practice Lead
Project Goal and Timeline
Approach
Tech Stack and Initial Architecture
Tools Selected
Realized Benefits
Agenda for Today
Let’s connect on LinkedIn!
linkedin.com/in/pchoe
Introduction.
Background.
TickPick offers “what you see is what you get”
pricing and a stellar customer experience.
3-year growth (Inc. 5000) - 393%
Meetup Promo Code - SAVE10
www.tickpick.com
www.youtube.com/tickpick
IPPON 2020
Project Goals.
Ippon 2019
Goals Solution
Drive insights from their data to
1. Increase Revenue
2. Gain 360° view of markets and
margins
3. Measure and increase effectiveness
of marketing campaigns
➔ World-class data analytics platform for the
purposes of empowering the business to
make informed decisions.
➔ Launchpad for kick-starting advanced Data
Science initiatives.
IPPON 2020
Continued
Model Training
Delivery Timeline.
- Data Pipelines,
- Streaming CDC,
- Release Pipelines,
- POCs
- Data pipelines from source systems into
the data lake and Snowflake
- CI/CD Pipelines
- Airflow
- Rata ingested from sources and loaded to
data warehouse
- In parallel, first data insights derived from
data and “test run” marketing campaigns
Realized up to 3X on
ROAS (Return on
advertising spend) with
new data backed
marketing campaigns
Expansion to
different business
use cases such as
Margin
Optimizations
Assessment
1st MVP up and running
1st Production Release
Week 1-3 Week 4-6 Week 10 Week 11-12 Week 12 +
3x ROAS
IPPON 2020
Data Landscape - 2019.
7.
Approach.
Focus on areas with biggest ROI
★ Business Intelligence
★ Data Warehouse
★ Data Orchestration & Data Movement
(ELT / ETL)
★ Data Catalog
★ Data Science
IPPON 2020
8. IPPON 2020
Guiding Principles.
★ Open Source First
★ Cloud Agnostic
★ Streamline Development - Integrate with CI/CD pipelines
★ Elasticity - Scale up when needed, and down when not
★ “Pay as you go” / Cost
★ Skill Set - Leverage existing staff’s skills to easily pick up new
technology / know how
Initial Architecture.
Centered on Web and Native
Mobile Apps
Reports and extracts were highly
manual with little to no
automation causing delays in
reporting metrics
Extracts were downloaded, then
loaded into excel then cut and
pasted into tables and pivot
tables
Excel graphs and visualizations
IPPON 2020
Before
Tech Stack.
❖ Azure
❖ C#
❖ Python
❖ Azure Service Bus
After
❖ Azure
❖ C#
❖ Python
❖ Azure Service Bus
❖ Azure Event Grid
❖ Stitch
❖ Airflow
❖ Snowflake
❖ Databricks
❖ Looker IPPON 2020
Tools Selected.
Requirements
❖
❖ Elasticity - horizontal and vertical scaling
❖ “Pay as you go”
❖ Cloud agnostic
❖ Easy to pick up
❖ Low operational costs
❖ Integrate-able
Tools Selected
❖ Snowflake
❖ Looker
❖ Python / Stitch
❖ Databricks
Key Functionalities
❖ Near Zero Maintenance
❖ Zero Copy Cloning
❖ Easy to integrate
❖ Fully
IPPON 2020
Realized Benefits.
Business
Intelligence
Looker
Fully integrated with Snowflake and
leverages Snowflake’s compute
capabilities
ELT
Stitch/Python
Ease of development
Reusable code
Direct connectivity to SaaS offerings
Data
Warehouse
Snowflake
Zero Copy Cloning
Near Zero Maintenance
Elasticity
Data Science
Databricks
Acceleration to delivery, easy
collaboration, fully integrated with
Azure
Data Catalog
Azure Data
Catalog
“Build for Today”
Allows for embedding key principles
and best practices.
Free to start, $1 per user otherwise
Ippon Technologies © 2017 13
What’s next?
Lessons Learned
❖ Build for today - Building a
enterprise solution takes time
and iterations
❖ Stand alone SQL vs Managed
Instances
❖ Managed Services vs
Operational Costs
Next Steps
❖ Never be satisfied, always room for
improvement
❖ Keep up to date with new changes to
landscape as things mature
❖ Astronomer
❖ Azure Services
➢ Synapse, Personalizer, ML Service
IPPON 2020
Questions?
pchoe@ipponusa.com
linkedin.com/in/pchoe
ippon.tech
IPPON 2020

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Greenfield data platform implementation

  • 2. IPPON 2019 Data Practice Lead at Ippon Technologies, a boutique consulting firm specializing in Data, Cloud, DevOps, and Application Development. Ippon has deep expertise across all major cloud platforms: AWS, Azure, and GCP. Nearly 20 years of data consulting experience across multiple industries, including Financial Services, Health and Life Sciences, and Media Previous clients include Morgan Stanley, FINRA, Warner Music, and McDonald's Corporation Patent Pending: Data Quality Analysis Tool Peter Choe U.S. Data Practice Lead Project Goal and Timeline Approach Tech Stack and Initial Architecture Tools Selected Realized Benefits Agenda for Today Let’s connect on LinkedIn! linkedin.com/in/pchoe Introduction.
  • 3. Background. TickPick offers “what you see is what you get” pricing and a stellar customer experience. 3-year growth (Inc. 5000) - 393% Meetup Promo Code - SAVE10 www.tickpick.com www.youtube.com/tickpick IPPON 2020
  • 4. Project Goals. Ippon 2019 Goals Solution Drive insights from their data to 1. Increase Revenue 2. Gain 360° view of markets and margins 3. Measure and increase effectiveness of marketing campaigns ➔ World-class data analytics platform for the purposes of empowering the business to make informed decisions. ➔ Launchpad for kick-starting advanced Data Science initiatives. IPPON 2020
  • 5. Continued Model Training Delivery Timeline. - Data Pipelines, - Streaming CDC, - Release Pipelines, - POCs - Data pipelines from source systems into the data lake and Snowflake - CI/CD Pipelines - Airflow - Rata ingested from sources and loaded to data warehouse - In parallel, first data insights derived from data and “test run” marketing campaigns Realized up to 3X on ROAS (Return on advertising spend) with new data backed marketing campaigns Expansion to different business use cases such as Margin Optimizations Assessment 1st MVP up and running 1st Production Release Week 1-3 Week 4-6 Week 10 Week 11-12 Week 12 + 3x ROAS IPPON 2020
  • 7. 7. Approach. Focus on areas with biggest ROI ★ Business Intelligence ★ Data Warehouse ★ Data Orchestration & Data Movement (ELT / ETL) ★ Data Catalog ★ Data Science IPPON 2020
  • 8. 8. IPPON 2020 Guiding Principles. ★ Open Source First ★ Cloud Agnostic ★ Streamline Development - Integrate with CI/CD pipelines ★ Elasticity - Scale up when needed, and down when not ★ “Pay as you go” / Cost ★ Skill Set - Leverage existing staff’s skills to easily pick up new technology / know how
  • 9. Initial Architecture. Centered on Web and Native Mobile Apps Reports and extracts were highly manual with little to no automation causing delays in reporting metrics Extracts were downloaded, then loaded into excel then cut and pasted into tables and pivot tables Excel graphs and visualizations IPPON 2020
  • 10. Before Tech Stack. ❖ Azure ❖ C# ❖ Python ❖ Azure Service Bus After ❖ Azure ❖ C# ❖ Python ❖ Azure Service Bus ❖ Azure Event Grid ❖ Stitch ❖ Airflow ❖ Snowflake ❖ Databricks ❖ Looker IPPON 2020
  • 11. Tools Selected. Requirements ❖ ❖ Elasticity - horizontal and vertical scaling ❖ “Pay as you go” ❖ Cloud agnostic ❖ Easy to pick up ❖ Low operational costs ❖ Integrate-able Tools Selected ❖ Snowflake ❖ Looker ❖ Python / Stitch ❖ Databricks Key Functionalities ❖ Near Zero Maintenance ❖ Zero Copy Cloning ❖ Easy to integrate ❖ Fully IPPON 2020
  • 12. Realized Benefits. Business Intelligence Looker Fully integrated with Snowflake and leverages Snowflake’s compute capabilities ELT Stitch/Python Ease of development Reusable code Direct connectivity to SaaS offerings Data Warehouse Snowflake Zero Copy Cloning Near Zero Maintenance Elasticity Data Science Databricks Acceleration to delivery, easy collaboration, fully integrated with Azure Data Catalog Azure Data Catalog “Build for Today” Allows for embedding key principles and best practices. Free to start, $1 per user otherwise
  • 13. Ippon Technologies © 2017 13 What’s next? Lessons Learned ❖ Build for today - Building a enterprise solution takes time and iterations ❖ Stand alone SQL vs Managed Instances ❖ Managed Services vs Operational Costs Next Steps ❖ Never be satisfied, always room for improvement ❖ Keep up to date with new changes to landscape as things mature ❖ Astronomer ❖ Azure Services ➢ Synapse, Personalizer, ML Service IPPON 2020