AI/ML
5 best practices for deploying ML models
In our previous article – 5 Challenges to be prepared for while scaling ML models, we discussed the top five challenges in…
5 challenges of scaling Machine Learning models
Machine learning on big data has opened the door to new opportunities to achieve business goals. It facilitates better ML modeling including…
Containerization of PySpark using Kubernetes
Containerization technology is widely used by data scientists and machine learning practitioners to promote the continuous deployment of models and test the…
Combining Big Data & Cloud for business transformation
Even after its introduction to the world in the 1970s by IBM, “cloud” was still a term used more by weatherman than…
Scoping Exercise for guaranteed Big Data project success!
Big projects with great teams fail. Yes, you read it correctly. Projects with proper funding clubbed together with great minds fail at…
CDP vs CRM: The key differences you need to know in 2019
Marketers around the world agree that modern-day marketing depends on customer data. Since we have a large amount of customer data at…
Customer Data Platform (CDP): A need or necessity?
Consumers today create a heap of data and digital footprints than ever before. Starting from geographical, transactional or behavioral data, to data…
Why B2B marketers need interactive analytics platform?
Your B2B marketing campaigns and programs generate a huge amount of data and dashboards are perhaps the best way to visualize, understand,…