PROOF OF CONCEPT IN WEEKS,DATA SOLUTION IN MONTHSImproving data-driven decision making

BobbyGill

PeteGrant

Sebastien Fabri

Where it started

Objectives

1. Provide a platform that allows future scalability, flexibility and agility to consume new customer data inputs.

2. Progressively consolidate customer data silos into a single customer view repository based on value.

3. Provide a platform that will allow more sophisticated analysis (e.g. predictive modelling).

4. Provide the business with self-service capability to key metrics and dashboards through the use of a data analytics and visualisation tool.

Platform Size

Implementation Approach1.Available platform and software services over

development and apparent control• Time is the most scarce resource• We’re not set up to COMPETE with AWS…

Services Without Commitment

More effective to use some of this…

Services Without Commitment…than to make our own from scratch

What We Actually Did Part 1• We used S3, Data Pipeline, EMR, Redshift -

the solution is AWS specific• We used Lambda which is AWS specific in that

it calls AWS services• We used CodeCommit• We used Jenkins as a scheduler

Implementation Approach1.Available platform and software services over

development and apparent control2.Creative assembly of services over product

customisation• Any one product might not satisfy all requirements• Customising products might not be the best option

Custom AssemblyCustom is better

Customising the product might work

But the gap isn’t usually just a paint job

What We Actually Did Part 2

Implementation Approach1.Available platform and software services over development and apparent control

2.Creative assembly of services over product customisation

3.Empowering the end user over charging for effort

• Avoid writing and reading specs• Cut out the middle men

What We Actually Did Part 3

GOVERNANCE

DATA

UI & VIZ

TRIGGEREMAIL

STREAM

API

Where Do We Start?

UI & VIZ

TRIGGEREMAIL

STREAM

API

MODELING LAYER(LookML)MP

P

How Do We Deliver It?

REDSHIFT DATA TEAM DATA PLATFORM END USERSINNOVATION

THE ECONOMIST

LOOKER

The Economist Implementation

REDUCED DATA PREPARATION AGILE DEV TRUST THE DATA EMPOWER

USERSNEW INSIGHTS

INNOVATION

THE ECONOMIST

LOOKER

The Economist Value

Time Lines

PoC.

Month 1 Month 2 Month 3 Month 4 Month 5-6

CEO requests for combined Data Vision

Internal reviews and requirements gatherings

PoC Built and tested!AWS Environment and Looker Dashboards

Business Review Road show

Building Business Case

Production

Month 8-9 Month 10 Month 11 Month 12

Production System Build - AWS

Internal Agile workshops - Identify the top 5 deliverables

Looker Dashboard build-Stick Rate reporting-Customer Journey

Phase 1 sign off and Phase 2 planning

Feedback

1. Our project lets us tie data together, leveraging data across the whole group, in order to spot practical, actionable insights. This information is crucial to our business.

2. The potential to drive real insight becomes suddenly considerably easier.3. We are now armed with facts and can set out priorities, i.e. to develop

features to our app and site to spur usage. 4. Cross-platform analysis, for the first time, we can begin to understand

the impact of registration and digital usage on conversion and retention

Questions?