AI/ML

Sigmoid
September 14, 2020

5 best practices for deploying Machine Learning models

In our previous article – 5 Challenges to be prepared for while scaling ML models, we discussed the top five challenges in…

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5-challenges-to-be-prepared-for-before-scaling-machine-learning-models
August 31, 2020

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…

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Containerization of PySpark
July 23, 2020

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…

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Big Data Cloud for business
July 2, 2019

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…

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Scoping Exercise for Big Data project success
May 24, 2019

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…

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CDP vs CRM
April 16, 2019

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…

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Customer-Data-Platform-CDP
April 3, 2019

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…

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Why B2B marketers need analytics platform
August 29, 2017

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,…

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