AI/ML
How to enhance cloud data security for financial institutions
Over the past few years, banking and capital market firms have increasingly realized that the cloud is more than just a solution…
Top 5 model training and validation challenges that can be addressed with MLOps
Digitalization turned from being an advantage into a necessity for organizations across the industries in the last couple of years. As the…
Why is data engineering critical to CPG marketing success
With most business processes transitioning to digital, the volume of data generated is witnessing exponential growth. Digital marketers today understand that the…
Build a winning data pipeline architecture on the cloud for CPG
The CPG industry has historically had little exposure to consumer data. But, with the surge in digitization and a shift in customer…
Deploying Machine Learning models with MLOps automation
The last few years have seen growing acceptance and adoption of ML and its increasing impact on other technological advancements. The majority…
Using Datawig, an AWS deep learning library for missing value imputation
While training a Machine Learning model the quality of the model is directly proportional to the quality of data. However, in some…
Best practices for adopting multicloud strategy in your organization
Companies today stand at the threshold of a cloud revolution. The shift towards hybrid/multi-cloud architectures has allowed companies to select more than…
Striking a balance between data privacy and personalization with marketing analytics
The proliferation of digital media has already had a profound impact on how consumers engage with companies. More recently, the COVID-19 pandemic…
Creating a transparent and resilient supply chain with analytics
As companies start resuming operations globally following the pandemic hiatus, the impact of a prolonged period of supply chain disruption has started…