Rethinking The Framework for Data, a CDO perspective

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In this talk, I discuss how enterprises should build a data management framework that helps them translates data into revenue-generating products. I explore best practices for each stage of the entire data lifecycle, from data capture to business insights, to enable positive AI-driven outcomes. You will learn how you should be thinking about getting value from data, in your own organization as a CDO. Video can be found on: https://exchange.scale.com/home/videos/rethinking-the-framework-for-data-with-chu-cheng-hsieh-of-etsy

Technology

Chu-Cheng Hsieh
Chief Data Officer, Etsy

?
?
?
?
?
L1: Collect & Monitoring
Future
?

Connect to data
source
Log & record
internal and
external events
Data quality
checks
L1: Collect &
Monitoring

Connect to data
source
Log & record
internal and
external events
Data quality
checks
Missing values
Abnormal values
(schema
evaluation)
Inconsistency
(versioning)
L1: Collect &
Monitoring

?
?
?
?
L2: Move, Transform, Store
L1: Collect & Monitoring
Future
?

Controlling cost: data
Storage, computation (ETLs)
From Unstructured to
Structured data
Metadata Generation
L2: Move, Transform,
Store

?
?
?
L3: Discover & Explore
L2: Move, Transform, Store
L1: Collect & Monitoring
Future
?

DATA SEARCH &
DISCOVERY PLATFORM
VALIDATION VISUALIZATION
(DASHBOARD)
L3: Discover &
Explore

?
?
L4: Aggregate
L3: Discover & Explore
L2: Move, Transform, Store
L1: Collect & Monitoring
Future
?

FEATURE STORES
(OFFLINE & STREAMING)
METRICS AGGREGATION
FUNCTION (REPORTS)
L4: Aggregate

?
L5: Model
&Experiments
L4: Aggregate
L3: Discover & Explore
L2: Move, Transform, Store
L1: Collect & Monitoring
Future
?

MACHINE LEARNING
(FORECASTING, OUTLIER
DETECTION, ETC.)
A/B TESTS (EXPERIMENTS) AI APPLICATIONS
(PERSONALIZED
MARKETING, ETC.)
L5: Model
&Experiments

L6:Insight
L5: Model
&Experiments
L4: Aggregate
L3: Discover & Explore
L2: Move, Transform, Store
L1: Collect & Monitoring
Observability,
Governance,
Automation

(& Action)
EXPLAIN ANALYTICS ACTIONS BASED ON
INSIGHTS
L6:Insight

L6:Insight
L5: Model
&Experiments
L4: Aggregate
L3: Discover & Explore
L2: Move, Transform, Store
L1: Collect & Monitoring
Future?

Observability, Governance, Automation
OBSERVABILITY GOVERNANCE AUTOMATION

Rethinking The Framework for Data, a CDO perspective

Drive the business with your KPIs. That is what we aimed to do at OVH. As a 18 years old company and quite big cloud provider, we encountered several issues during this long journey to setup change data capture and data driven culture. Getting data from thousands of tables into one place, keep it all up to date was not possible without a strong streaming engine like Apache Flink. We will present you our current production pipeline with its pros and cons. From the data collection made directly with binary logs of the databases, to continuous writing into Apache Hive in a Kerberized cloud-based Apache Hadoop cluster. We will describe how we handle schema transcription, events lifecycle, stream partitioning, sort of the events with the use of watermarks and windows aggregation - all of this in a transaction way until the data availability on user side. Finally we will introduce our production infrastructure based on cloud only, its operation and monitoring.

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Rethinking The Framework for Data, a CDO perspective

1. Chu-Cheng Hsieh Chief Data Officer, Etsy

3. ? ? ? ? ? L1: Collect & Monitoring Future ?

5. Connect to data source Log & record internal and external events Data quality checks L1: Collect & Monitoring

6. Connect to data source Log & record internal and external events Data quality checks Missing values Abnormal values (schema evaluation) Inconsistency (versioning) L1: Collect & Monitoring

7. ? ? ? ? L2: Move, Transform, Store L1: Collect & Monitoring Future ?

8. @Copyright: Andreas von der Heydt

9. Controlling cost: data Storage, computation (ETLs) From Unstructured to Structured data Metadata Generation L2: Move, Transform, Store

10. ? ? ? L3: Discover & Explore L2: Move, Transform, Store L1: Collect & Monitoring Future ?

11. DATA SEARCH & DISCOVERY PLATFORM VALIDATION VISUALIZATION (DASHBOARD) L3: Discover & Explore

12. ? ? L4: Aggregate L3: Discover & Explore L2: Move, Transform, Store L1: Collect & Monitoring Future ?

13. REUSABLE MODULARS

14. FEATURE STORES (OFFLINE & STREAMING) METRICS AGGREGATION FUNCTION (REPORTS) L4: Aggregate

15. ? L5: Model &Experiments L4: Aggregate L3: Discover & Explore L2: Move, Transform, Store L1: Collect & Monitoring Future ?

16. MACHINE LEARNING (FORECASTING, OUTLIER DETECTION, ETC.) A/B TESTS (EXPERIMENTS) AI APPLICATIONS (PERSONALIZED MARKETING, ETC.) L5: Model &Experiments

17. L6:Insight L5: Model &Experiments L4: Aggregate L3: Discover & Explore L2: Move, Transform, Store L1: Collect & Monitoring Observability, Governance, Automation

18. (& Action) EXPLAIN ANALYTICS ACTIONS BASED ON INSIGHTS L6:Insight

19. L6:Insight L5: Model &Experiments L4: Aggregate L3: Discover & Explore L2: Move, Transform, Store L1: Collect & Monitoring Future?

20. Observability, Governance, Automation OBSERVABILITY GOVERNANCE AUTOMATION

21. L6:Insight L5: Model &Experiments L4: Aggregate L3: Discover & Explore L2: Move, Transform, Store L1: Collect & Monitoring Observability, Governance, Automation

Editor's Notes

Image by <a href="https://pixabay.com/users/bru-no-1161770/?utm_source=link-attribution&utm_medium=referral&utm_campaign=image&utm_content=1308138">Bruno /Germany</a> from <a href="https://pixabay.com/?utm_source=link-attribution&utm_medium=referral&utm_campaign=image&utm_content=1308138">Pixabay</a>
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Garbage In Garbage Out

Rethinking The Framework for Data, a CDO perspective

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Editor's Notes