Data Management
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…
Data-driven revenue growth management for CPGs
Consumer Packaged Goods (CPG) companies are undergoing massive transformation on multiple fronts — changing consumer behavior, new supply chain practices, increasing competition…
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…
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…
Role of AI/ML in enhancing overall equipment effectiveness for Industry 4.0
The manufacturing industry has historically been a hotbed of innovation. And, manufacturers have always pursued greater speed, scale, and simplicity across operations…
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 multi-cloud 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…
5 ways IoT-based predictive maintenance generates business value
The ability to predict faults and address them before they reach critical condition is indispensable, and being able to perform maintenance while…
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…