COMMON SENSE
Data & Analytics
New York 2022

Jay Suites Midtown East
November 15th, 2022, 9:30 am - 7 pm, Successfully held

A conversational conference for Data Leaders focused on transformative data infrastructure and the analytic value that transformation creates.

COMMON SENSE
Data & Analytics
New York 2022

Jay Suites Midtown East
November 15th, 2022,
9:30 am - 7 pm, Successfully held

A conversational conference for Data Leaders focused on transformative data infrastructure and the analytic value that transformation creates.

What we will discuss at
COMMON SENSE

Data & Analytics
New York 2022

The avalanche of data generated by companies and their customers should be a competitive advantage, but most companies are struggling to manage it all. There aren’t any simple answers, but emerging frameworks are helping us catch up with the growth in data. In this conference, we will focus on the role of new models for data infrastructure and the new ways and reasons to invest in data analytics.

Who Should Attend

Our conference is designed for 70 IT leaders responsible for their company’s data infrastructure, data strategy and analytics strategy, including CTO’s, Chief Architects, Heads of Software Engineering, Data Analytics leaders, Chief Data Officers and Chief Digital Officers from innovative enterprises in North America.

AGENDA

9:30 am – 9:45 am

Registration

9:45 am – 10:15 am

Welcome Address & Sponsor Intro

10:20 am – 11:10 am

Panel Session

Moderated by

AnswerRocket

Why AI/ML advanced analytics projects fail

Advanced analytics projects using ML are inherently complex with multiple points of failure. Companies can improve the likelihood of success by avoiding the most common stumbling blocks. Some of these include:

  • Model maintenance challenges
  • Lack of data governance
  • Model testing & validation

In this session, we’ll explore ways companies are improving the odds of success for advanced analytics initiatives.

Moderator
Mike Finley
Co Founder at AnswerRocket

11:15 am – 12:30 pm

Networking & Sponsor Meetings

12:30 pm – 1:10 pm

Lunch

1:15 pm – 2:05 pm

Panel Session

Moderated by

Acceldata

Identifying root causes of data quality problems

When incorrect data is discovered, companies react with data profiling and data cleansing and typically build a plan to avoid repeating the mistakes that led to it.

However, data quality issues are much more challenging to resolve when they span the enterprise. 3 common challenges create data quality issues and make it difficult to resolve them:

  • Not treating data as an enterprise asset
  • Executive management indifference
  • No time to implement & monitor best practices

In this session we’ll discuss how data leaders are overcoming these challenges in their companies.

Moderator
Girish Bhat
Senior Vice President Marketing
at Acceldata

2:10 pm – 3:00 pm

Panel Session

Moderated by

Dremio

Will cloud ecosystems make insight to action a reality in 2023 & beyond?

Insights disconnected from action aren’t very valuable. If insights from ingested data don’t feed back into operational systems like CRM or marketing automation, the insights either go unused or require massive manual effort. Modern cloud ecosystems and APIs are now at the point where this problem can be solved without a massive development effort.

In this session, we’ll discuss ways in which companies are finally turning insights into action by leveraging cloud ecosystems. What tooling is most valuable? What pitfalls should you be on guard against?

3:05 pm – 4:20 pm

Networking & Sponsor Meetings

4:25 pm – 5:15 pm

Panel Session

Moderated by

dotData

When should companies go all-in on Machine Learning?

Many companies waste money and resources applying machine learning to challenges that simple SQL will solve. How do you decide when it’s time to make the investment in resources to build solutions that actually require ML? The most common answer is that you need to make data-driven predictions for your company. Some indicators we’ll discuss:

  • Do you need to influence trends you’ve seen in historical data before they happen again?
  • Are you looking at ways to apply statistical analysis to your data beyond the capability of SQL?
  • Do you need to analyze new data sources that don’t work in your data warehouse?

In this session, we’ll discuss how companies with large data volumes can decide if it’s time to embrace the ML stack.

Moderator
Radesh Ganeshkumar
Vice President of Global Sales
at dotData

5:20 pm – 7:00 pm

Cocktails & Networking

Some of our Speakers

Hao Tong
Director of Data Science at FanDuel
LinkedIn
Casey Rattay
Director, Data at Equinox
LinkedIn
Vishnu Chelle
Product Director, R&D Data Platform APIs at GSK
LinkedIn
Ravi Elaprolu
Director, Data & MLOps, Inventory Management at GAP
LinkedIn
Suryakant Brahmbhatt
Executive Director at Morgan Stanley
LinkedIn
Jessica Xu
Managing Director, Data Science at OneMain Financial
LinkedIn
Mike Murtha
Director, Data Exchange at Highmark Health
LinkedIn
Glen Gomez Zuazo
Senior Director IT Architecture at E*TRADE
LinkedIn
Ketan Pardal
Head of BI & Analytics at Citizens Financial Group
LinkedIn
Deepak Jose
Global Head of ODDA Analytics Solutions & Senior Director at Mars
LinkedIn
Ashmi Turakhia
Business Intelligence and Analytics Leader at rue21
LinkedIn
Suzanne Marzziotti
Director – Insights and Analytics at Novartis
LinkedIn
Amar Drawid
Global Head of Data Science & Infrastructure – Executive Director at Novartis
LinkedIn
Yin Aphinyanaphongs
Director, Operational Data Science and Machine Learning at NYU Langone Health
LinkedIn
VENUE

Jay Suites Midtown East

515 Madison Avenue
10th Floor
New York, NY 10022