This document discusses use cases for a modern data platform. It begins by outlining the agenda, then provides background on Altis, the consulting firm. The document defines a modern data platform and explains how it differs from traditional setups. It discusses three approaches for selecting initial use cases: lift and shift with a twist, hitting a roadmap milestone, and supporting an organizational strategy. Examples are provided of where each approach has worked and struggled. The document covers design patterns, managing costs, and identifying success criteria for use cases.

1. USE CASES FORTHE MODERN DATA PLATFORM
THE FUTURE OF DATA & ANALYTICS
Alex Gray (Regional Manager) May 2020
alexg@altis.co.nz
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2. AGENDA
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• Welcome
• What is a modern data platform
• How is this different from a traditional set up
• Separating out use case from delivery approach
• The three approaches with choosing use cases
• Where those approaches have worked
• Where they have struggled
• How do Design Patterns come into play with a
Modern Data Platform
• How have organisations managed their costs
• Picking Native PaaS vs 3rd party PaaS
components for your use case
• How to identify what “success” for a use case
looks like
• Q & A
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3. Australia and New Zealand’s largest
privately owned Data & Analytics
consultancy
For 22 years, we have been combining
industry expertise with technical capability
to deliver tangible business outcomes while
maintaining the Altis ethos of Connecting
with Courage, Heart and Insight.
Established in 1998
Offices in Sydney, Brisbane, Melbourne,
Canberra, Auckland and London
Vendor independent
ABOUT ALTIS
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4. Altis NAMED IN GARTNER’S MARKET GUIDE
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For the second year in a row, Altis Consulting has been recognised in
Gartner Inc.’s “Market Guide for Data and Analytics Service Providers”.
The report identifies service providers with a proven track record of
delivering successful analytics programs.
Altis’ CEO, John Hoffman said, “Our inclusion in the Gartner report
reaffirms our position as the leading data and analytics service provider
in Australia and New Zealand. Our focus on utilising industry expertise,
modern technologies, and repeatable patterns to accelerate the delivery
of tangible business outcomes for our clients continues to shine through.
We are delighted to be acknowledged again.”

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WHAT: is a Modern Data
Platform
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6. 6
What is a modern data platform
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What is a modern data platform - Roadmap
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What is a modern data platform – Data Design
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WHY: is this important
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What is a modern data platform – Maturity
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Microsoft’s data and analytics maturity curve Gartner’s recommendations and maturity stages

11. Not just technology

12. How is this different from a traditional set up
• Flexibility
• Scale
• Tailored Design
• Cost

13. Time to action is
shortened through
repeatable
machine-centered
analysis
Recap: Human vs Machine decision making and
automation
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HOW: picking the initial use
cases
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15. Separating out use case from delivery approach
• Be careful of how you are interlaying delivery over the top of use cases
• CI/CD
• Agile Delivery
• DataOps
• Don’t have delivery as a use case, that is an implementation style

16. The three types of initial use case
• Lift and Shift with a twist
• Taking something that exists and:
• Adding additional source systems
• Making it run more often
• Storing it in a different data format (ie data lake)
• Like for Like Lift and Shift is not a “use case”, it’s an approach

17. The three types of initial use case
• Hitting a Roadmap milestone
• Machine Learning
• Artificial Intelligence
• Chatbot
• IoT

18. The three types of initial use case
• An important win for the organisations strategy
• We have this new direction for the business, we might as well tie to this new
platform

19. Where those approaches have worked
• Lift and Shift with a twist
• Streaming some data that will give users valid information at the time that they
need to make a decision. Feeding live data into some easier to calculate KPI’s,
will give an organisation, the benefits of seeing what real time information can
do to their business
• Hitting a Roadmap milestone
• There was enough data of good enough quality to get the results that the
organisation was then able to trust that it would be good enough to validate
results. In Machine Learning, initial use cases should augment the decision
process, not automate it. It should give decision makers, better information to
give a better educated decision, not remove that decision from being made.
• An important win for the organisations strategy
• Where the strategy is small enough that it is manageable, it should ideally be a
lower level strategy, as not all use cases in the Modern Data Platform, will
return immediate benefits.

20. Where organisations have struggled
• Lift and Shift with a twist
• Moved from 15 minute refreshes for existing reporting to 5 minutes in new
Modern Data Platform. 5 minute refreshes didn’t give any additional value, but
cost significant dollars to run ongoing.
• Real time reporting through streaming, can also cause issues for the business
then understanding why all reporting can’t then be real time.
• Hitting a Roadmap milestone
• The data wasn’t there to support the Machine Learning outcome that was
desired. The outcome wasn’t statistically accurate enough to give value and
thus deemed a failure, putting Machine Learning on hold for an additional 12
months
• An important win for the organisations strategy
• The strategy was important to the organisation and got lots of visibility, but the
business process wasn’t ready to support down stream usage. This is a
misalignment of tactics to strategy

21. Prioritisation
• Identify 3-5 use cases for each of the 3 types and prioritise

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HOW: managing costs
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23. How do Design Patterns come into play

24. How have organisations managed their costs
• Initial IT Driven spend bucket
• Business Unit driven
• Project Driven

25. Picking Native PaaS vs 3rd party components
• 3rd part components play an important part with:
• Controlling costs
• Better integration
• Tailored to easier development
• Our experience is to try native PaaS, understand the areas of concern and make an
informed decision.

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HOW: understanding success
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27. How to identify what “success” looks like
• Prove the benefit
• Need to understand cost and how to account for it
• Need to understand how the implementation ongoing would look like
• Need to give the business additional value from their current state

28. QUESTIONS
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