Alluxio Monthly Webinar | Five Disruptive Trends that Every Data & AI Leader Should Understand

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Alluxio Monthly Webinar Jan. 30, 2024 For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - Kevin Petrie (VP of Research, Eckerson Group) - Omid Razavi (SVP of Customer Success, Alluxio) 2024 is gearing up to be an impactful year for AI and analytics. Join us on January 30, as Kevin Petrie (VP of Research at Eckerson Group) and Omid Razavi (SVP of Customer Success at Alluxio) share key trends that data and AI leaders should know. This event will efficiently guide you with market data and expert insights to drive successful business outcomes. - Assess current and future trends in data and AI with industry experts - Discover valuable insights and practical recommendations - Learn best practices to make your enterprise data more accessible for both analytics and AI applications

Software

© Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com
Kevin Petrie
VP Research
Five Disruptive Trends that Every
Data & AI Leader Should Understand
January 30, 2024
Omid Razavi
SVP Customer Success

© Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com
Today’s Speakers
25+ years in tech
Teach early adopters about AI,
data, and analytics
Servant leader, writer, editor,
listener, and speaker
linkedin.com/in/kevinpetrietech/

© Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com
Disruptive Data & AI Trends of 2024
Data, AI, and IT leaders must optimize hardware, software, and dollars
to meet modern business requirements
APPLICATIONS &
WORKFLOWS
DATA PIPELINES
DATA STORES
INFRASTRUCTURE
COST
GOVERNANCE
AI/ML matures from project to must-have feature
Pipelines transform & deliver new data to new models
Distributed datasets conflict with latency requirements
GPU scarcity drives need for higher utilization
FinOps programs help govern cloud-related costs

© Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com
GPU Scarcity Drives Need for Higher Utilization
Data, AI, and IT leaders must maximize GPU cycles during runtime and minimize the rest
APPLICATIONS &
WORKFLOWS
DATA PIPELINES
DATA STORES
INFRASTRUCTURE
COST
GOVERNANCE • Optimize software algorithms with efficient
design and deployment
• Implement dynamic scaling to consume
GPUs only as needed
• Adopt cloud-based GPUs to avoid idle
onsite systems

© Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com
Distributed Datasets Conflict with Latency Requirements
Data, AI, and IT leaders must synchronize compute and storage resources
APPLICATIONS &
WORKFLOWS
DATA PIPELINES
DATA STORES
INFRASTRUCTURE
COST
GOVERNANCE • Modern analytics use cases require
real-time processing
• Hybrid and multi-cloud environments
cannot meet these SLAs
• Distributed caching, unified namespace,
and metadata can accelerate workloads

© Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com
Pipelines Transform and Deliver New Data to New Models
Data, AI, and IT leaders must adapt their environments
to support new data types and analytics use cases
APPLICATIONS &
WORKFLOWS
DATA PIPELINES
DATA STORES
INFRASTRUCTURE
COST
GOVERNANCE • New AI/ML models require new datasets and
preparation methods
• Design scalable, flexible data pipelines
• Foster agile data practices and team
collaboration

© Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com
AI/ML Matures from Project to Must-Have Feature
Data, AI, and IT leaders must synchronize diverse elements of their environments
APPLICATIONS &
WORKFLOWS
DATA PIPELINES
DATA STORES
INFRASTRUCTURE
COST
GOVERNANCE
• GenAI language models, predictive ML
become part of multi-faceted applications
• Derive insights and take actions based on
diverse inputs, models, and outputs
• This requires careful design and
orchestration of pipelines, models &
applications

© Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com
FinOps Programs Help Govern Cloud-Related Costs
Data, AI, and IT leaders must adapt their people, process, and technologies
to reduce the risk and variability of cloud-related costs
APPLICATIONS &
WORKFLOWS
DATA PIPELINES
DATA STORES
INFRASTRUCTURE
COST
GOVERNANCE
• Dynamic workloads and complex
environments lead to cost surprises
• FinOps helps forecast, measure, and
account for cloud resource consumption
• Instils best practices & automates
processes (resource monitoring,
chargeback, etc.)

© Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com
Guiding Principles for 2024
Master these five trends and play each to your advantage
AI/ML matures from project to must-have feature
Pipelines transform & deliver new data to new models
Distributed datasets conflict with latency requirements
GPU scarcity drives need for higher utilization
FinOps programs help govern cloud-related costs
Artificial intelligence creates new
opportunities but compounds risks
AI/ML initiatives depend on effective
data processing and delivery

© Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com
Questions?
I’m listening!

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ADR, or Architecture Decision Record, is a valuable tool in software development for several reasons. It provides a centralized location for documenting and tracking architectural decisions, aiding both current and future team members. ADRs enhance communication among team members by documenting the rationale behind architectural decisions, especially beneficial during onboarding of new team members or when revisiting decisions. They serve as a knowledge base, enabling teams to learn from past decisions and refine their decision-making process. Additionally, ADRs contribute to transparency by helping stakeholders understand the reasons behind specific architectural choices. As with any other tool or process, introducing them into an organization can face several obstacles, and overcoming these challenges is crucial for successful implementation. In this talk I go through some common problems and our way of solving them.

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Alluxio Monthly Webinar | Five Disruptive Trends that Every Data & AI Leader Should Understand

1. © Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com Kevin Petrie VP Research Five Disruptive Trends that Every Data & AI Leader Should Understand January 30, 2024 Omid Razavi SVP Customer Success

2. © Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com Today’s Speakers 25+ years in tech Teach early adopters about AI, data, and analytics Servant leader, writer, editor, listener, and speaker linkedin.com/in/kevinpetrietech/

3. © Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com Disruptive Data & AI Trends of 2024 Data, AI, and IT leaders must optimize hardware, software, and dollars to meet modern business requirements APPLICATIONS & WORKFLOWS DATA PIPELINES DATA STORES INFRASTRUCTURE COST GOVERNANCE AI/ML matures from project to must-have feature Pipelines transform & deliver new data to new models Distributed datasets conflict with latency requirements GPU scarcity drives need for higher utilization FinOps programs help govern cloud-related costs

4. © Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com GPU Scarcity Drives Need for Higher Utilization Data, AI, and IT leaders must maximize GPU cycles during runtime and minimize the rest APPLICATIONS & WORKFLOWS DATA PIPELINES DATA STORES INFRASTRUCTURE COST GOVERNANCE • Optimize software algorithms with efficient design and deployment • Implement dynamic scaling to consume GPUs only as needed • Adopt cloud-based GPUs to avoid idle onsite systems

5. © Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com Distributed Datasets Conflict with Latency Requirements Data, AI, and IT leaders must synchronize compute and storage resources APPLICATIONS & WORKFLOWS DATA PIPELINES DATA STORES INFRASTRUCTURE COST GOVERNANCE • Modern analytics use cases require real-time processing • Hybrid and multi-cloud environments cannot meet these SLAs • Distributed caching, unified namespace, and metadata can accelerate workloads

6. © Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com Pipelines Transform and Deliver New Data to New Models Data, AI, and IT leaders must adapt their environments to support new data types and analytics use cases APPLICATIONS & WORKFLOWS DATA PIPELINES DATA STORES INFRASTRUCTURE COST GOVERNANCE • New AI/ML models require new datasets and preparation methods • Design scalable, flexible data pipelines • Foster agile data practices and team collaboration

7. © Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com AI/ML Matures from Project to Must-Have Feature Data, AI, and IT leaders must synchronize diverse elements of their environments APPLICATIONS & WORKFLOWS DATA PIPELINES DATA STORES INFRASTRUCTURE COST GOVERNANCE • GenAI language models, predictive ML become part of multi-faceted applications • Derive insights and take actions based on diverse inputs, models, and outputs • This requires careful design and orchestration of pipelines, models & applications

8. © Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com FinOps Programs Help Govern Cloud-Related Costs Data, AI, and IT leaders must adapt their people, process, and technologies to reduce the risk and variability of cloud-related costs APPLICATIONS & WORKFLOWS DATA PIPELINES DATA STORES INFRASTRUCTURE COST GOVERNANCE • Dynamic workloads and complex environments lead to cost surprises • FinOps helps forecast, measure, and account for cloud resource consumption • Instils best practices & automates processes (resource monitoring, chargeback, etc.)

9. © Eckerson Group 2021 Twitter: @eckersongroup www.eckerson.com Guiding Principles for 2024 Master these five trends and play each to your advantage AI/ML matures from project to must-have feature Pipelines transform & deliver new data to new models Distributed datasets conflict with latency requirements GPU scarcity drives need for higher utilization FinOps programs help govern cloud-related costs Artificial intelligence creates new opportunities but compounds risks AI/ML initiatives depend on effective data processing and delivery

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