Webinar
Dangers of Homogeneous Sampling – How Your Data May Be Telling You the Wrong Story
Save your spot!
January 16th, 2025 | 11:30 | ONLINE
About this Series
Diversity in Data is a groundbreaking webinar series showcasing professionals from diverse backgrounds who are driving innovation in data science, analytics, and technology. Each session explores cutting-edge trends, ethical challenges, and emerging technologies through inclusive, dynamic conversations.
Join us for the inaugural event to gain fresh insights and strategies from leading BIPOC voices shaping the future of data.
Join the Conversation with BIPOC Experts in Data
Are your data insights reliable, or could they be leading you astray? Homogeneous sampling—data drawn from narrow or similar groups—often introduces significant bias into analyses, skewing insights and resulting in faulty decision-making.
In this thought-provoking discussion, our seasoned data experts will explore the dangers of homogeneous sampling, its impact on business decisions, and actionable steps to ensure your data truly reflects reality.
Webinar Details
Topic
Dangers of Homogeneous Sampling: How Your Data May Be Telling You the Wrong Story
Date & Time
January 16th, 2025 @ 11:30 pm
Format
Panel discussion + Q&A
(25 minutes discussion + 10 minutes Q&A)
Cost
Free
Duration
35 Minutes
Webinar Details
Topic
Dangers of Homogeneous Sampling: How Your Data May Be Telling You the Wrong Story
Date & Time
January 16th, 2024 @ 11:30 pm
Format
Panel discussion + Q&A
(25 minutes discussion + 10 minutes Q&A)
Cost
Free
Duration
35 Minutes
Meet the Experts
Nadji Bessa
Director of Engineering
@ Infostrux
Nadji is a seasoned engineering leader with over 15 years of experience in software development and data engineering, specializing in building scalable data solutions and leading cross-functional teams to drive innovation.
Anirban Aikat
Principal, Data Management
@ Infostrux
Anirban specializes in data governance and strategy, helping businesses unlock the power of their data.
Haleemur Ali
Principal, Data Engineering
@ Infostrux
Hal specializes in scalable data architectures, helping organizations turn complex datasets into actionable insights.
What You'll Learn
Understanding Sampling Bias
How homogeneous sampling introduces hidden biases and leads to misleading insights.
Detecting Homogeneity in Your Data
Practical strategies for identifying when your sample lacks diversity and how it impacts your analysis.
Broader Business Implications
Real-world examples of how homogeneous sampling caused significant business missteps—and how to avoid them.
Practical Solutions and Best Practices
Expert tips on expanding your sampling methods for more robust and representative data.
Tools for Improved Data Collection
Explore advanced techniques and tools to diversify your data sources and enhance the quality of your insights.
Why This Matters?
Homogeneous sampling isn’t just a technical oversight—it’s a critical risk to your organization’s decision-making process. Join us to ensure your insights reflect the full story, not just one part of it.
Reserve Your Spot Today
Seats are limited—secure your place now to join this impactful conversation.
Who Should Attend?
- Data analysts, engineers, and scientists
- Business leaders and decision-makers
- Professionals interested in ethical and accurate data practices
- Anyone looking to enhance their understanding of sampling diversity