Here is my look at leveraging real-time analytics.

1. Leveraging Real-Time
Analytics as part of
driving Data and AI to
Improve Business
Outcomes
SENIOR DATA AND AI TECHNICAL EXPERT
– PAUL YOUNG CPA CGA

2. Paul Young –Senior
Data and AI Expert
• CPA, CGA (1996)
• Academia (PF1, FA4, FN2, MU1. and MS2)
• SME – Customer Success Management
• SME – ESG and Sustainability Reporting
• SME – Risk Management
• SME – Close, Consolidate and Reporting
• SME – Public Policy
• SME – Emerging Technology
• SME – Business Process Change
• SME – Financial Solutions
• SME – Macro/Micro Indicators
• SME – Supply Chain Management
• SME – Data, AI, Security, and Platform
• SME – Internal Controls and Auditing
Contact information email: Paul_Young_CGA@outlook.com
LinkedIn: https://www.linkedin.com/in/paul-young-055632b/
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3. Agenda
Addressing Data Silos
Addressing Data Management and Storage
Having the right Data Strategy
What are real-time analytics
Who uses real-time analytics
Key real-time analytics databases
How to best to implement real-time Analytics
Generic data architecture diagram
Recommended Practices / Real-Time Analytics
What is next

4. Addressing
Data Silos
Source -
https://www.talend.com/resources
/what-are-data-silos/

5. Address Data
Management
and Storage
Looking at the best ways to secured
and store data for an organization
Cloud first strategy continues to be
focus by many organizations
Top Cloud Storage Solutions

6. Having the
right Data
Strategy

7. What are real-
time data
analytics?

8. Who uses
Real-Time
Analytics

9. Key Real-Time
Database
Vendors
1. Mongo DB
2. Microsoft
3. Google
4. Oracle
5. Cloudera
6. MariaDB
7. Singlestore DB
8. Databricks
9. AWS Synapse
10. Snowflake

10. How to
implement
real-time
analytics
1. Understand what you need. Before implementing real-
time analytics into your business, you need to have a
clear idea of your company's needs. ...
2. Pinpoint data sources precisely. ...
3. Build your data infrastructure. ...
4. Choose the best real-time analytics tool.

11. Generic
Diagram /
Data
Architecture

12. Real-time
Analytics /
Recommended
Practices

13. What is next?
1. Identifying the use case for real-time analytics -
https://www.striim.com/blog/real-time-analytics-use-
cases-and-examples/
2. Data strategy including evaluated current data
management (Capturing, securing, storing, governance,
ingestion, and analytics)
3. Look at doing a proof of concept with small data set as
part of building out the real-time analytical solutions