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Data Transfer Challenges In Evaluating MLOps Platforms

Posted Jan 06
# Research
# Systems and Architecture
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SPEAKER
Pardis Noorzad
Pardis Noorzad
Pardis Noorzad
Head of Data Science @ Carbon Health

Pardis Noorzad is an executive with 14 years of experience building effective teams and quality products. She built the Data Science function at Carbon Health, driving all data initiatives as the company grew 45X. Pardis led a data team at Twitter, covering 80% of consumer products. In addition to healthcare and social media, Pardis built products in fintech (at Paytm) and in e-commerce (Hong Kong, Europe, and Canada markets).

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Pardis Noorzad is an executive with 14 years of experience building effective teams and quality products. She built the Data Science function at Carbon Health, driving all data initiatives as the company grew 45X. Pardis led a data team at Twitter, covering 80% of consumer products. In addition to healthcare and social media, Pardis built products in fintech (at Paytm) and in e-commerce (Hong Kong, Europe, and Canada markets).

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SUMMARY

Customers evaluating MLOps platforms as a service need to provide customer data during the evaluation phase. The data often needs to be moved to the MLOps companies' warehouses. This is not a simple task and can become costly if the two partners are using different cloud service providers. Apart from the challenges of data transfer, there is also the matter of compliance and privacy. For sensitive data, a secure transfer is not enough, and masking and other anonymization measures need to be implemented. In this talk, we review the myriad roadblocks faced by companies evaluating MLOPs platforms in providing access to their data for evaluation purposes. Further, we discuss some potential solutions.

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