Date: 15th November 2017 Location: AI Lab Theatre Time: 14:30 - 15:00 Speaker: Simon Ricketts / Dimitris Pertsinis Organisation: SYNTASA / TMG

1. Unleash Data Science
Across Your Organisation
Simon Ricketts
Customer Engagement Director
SYNTASA
Dimitris Pertsinis
Head of Data Science
Telegraph Media Group

2. 2
Predictive Behavioral Analytics Dataflow
INPUT
ADAPTORS
PREDICTIV
E MODELS
DoubleClick
Google
Analytics
Adobe
Clickstream/
Livestream
In-Store
Transactions
. . .
Buying
Behavior
Product
Recommendation
Purchase/
Churn
Likelihood
Offer
Response
Likelihood
. . .
OUTPUT
ADAPTORS
DMP
Adobe
Marketing
Cloud
Email
Automation
CRM
. . .
Unified
Customer
Intelligence
Consolidated
Behavioral
Schema
+
Identity
Resolution

3. 3
Extending the Marketing Cloud
Application
2nd/3rd Party Data
Marketing Cloud
AdvertisementsPersonalisation Communications
PersonalisationData Management
Platform
Email CampaignProfiles & AudiencesAnalytics
Enterprise Data Platform
EmailEPOSERPLoyalty
Digital Events CRM Inventory Call Center

4. 4
Financial Services GovernmentRetail & Ecommerce Media
Industries We Serve

5. What This is About

6. The Key Points
- The Ball on DS Court (Learning to Swim )
- Post Lake Issues
- Deploying Software
- Unleashing DS
6

7. What This is Not About

8. The Key Non Points
- An in Depth Comparison of Infrastructures (Hadoop Vs GCP Vs AWS)
- Yet Another Overview of the DS Hierarchy of Needs or Maturity Model
- Prescriptive Success
- Complaining
(Maybe Some)
8

9. A History of DS at The
Telegraph

10. Pre Lake
- Interest in Data Science, Team assembled.
- Getting any Significant Project Required Weeks of Data Herding
- Hard to Offer Value with Disparate Data Sets and Lack of Clarity on Schemas
- Investment is Required to Supercharge Returns
- Bring That Data In – Design it so it is not as Disparate
- Day 0 – Date Lake Delivered

11. Post Lake Blues

12. Post Lake
In at the Deep End
- Business Invested Now Wants Return
- New Data Sources in to Lake at Rate of
1-2 p/w
- Design Allowed for Deterministic
joining of Most Sources
- Team of Data Engineers Assembled
- New Kinds of Silos
- Lack of Documentation
- Technology Start Building Products on
Top
- Data Engineers Become Resource Gold
- Prototyping Faster – Lack of
Familiarity With Datasets Adding Time
12

13. Deploying Software
An Interlude

14. Deploying Syntasa
From a Naïve Observer
- Pre Lake Decision to go With GCP and BQ. Reasons:
- Lack of Maintenance Overhead
- Resource Allocation – Speed (~1 Minute to Setup Cluster and Deploy Code)
- Cost
- Previous Employer on Premise Hadoop (on lockdown)
- Difference in Speed of Deployment and Processing Massive
- Access to Outside World - Edge Node on Lockdown

15. Unleash Your DS Team
Our Time Has Come

16. Unleash Your Team
- Automate Data Consolidation, Data Validation, Data Transformation
- Consolidate Front End, Back End System and Service Data
- Minimize Your Data Exploration and Data Cleaning Day to Hours
- Free Team’s Time to Allow Better Prototyping
- Optimise the Time Your Data Engineers Need to be Involved

17. Questions