Why Data Science Needs DataOps
DataOps helps reduce the time data scientists spend preparing data for use in applications. Such tasks consume roughly 80% of their time
Topic: From Our Experts
Top articles from our RTInsights Experts
5 DevOps Trends That Demand Your Attention
DevOps today plays an increasingly important role as businesses must rapidly develop, deploy, and update applications to keep pace with ever-changing customer …
How Today’s Microservices are Building Tomorrow’s Cloud
Microservices help developers deliver new features more quickly and effectively than ever before to keep giving users what they
Powering Smart Supermarket Shelves: A Shopping Transformation
The bulk of supermarket purchases are still primarily made in-store; personalized in-store shopping experiences are the next logical frontier for digital …
For True Digital Transformation Organizations Must Think Bigger
For true, end-to-end digital transformation, companies need to think bigger and make the important shift in mindset from task automation to process
Say Goodbye to Performance Benchmarks and Hello to Efficiency Benchmarks
Many enterprises are realizing that the price tag of moving to the cloud can get pretty high, and are looking to implement cost controls.
IoT May be a Hacker’s Delight, Both Inside and Out
Securing IoT devices and staying ahead of certificate expiration have become top strategic priorities for IT
R and Python: Critical Programming Languages to Begin Your Data Science Career
R and Python are the two most widely used programming languages by data scientists worldwide. However, based on their preference, they may choose what best …
Four Intelligent Automation Methodologies – One Objective
The methodologies are complementary, have commonalities, require different skills, and should be part of the overall meta-iterations within a concerted digital …
Why People Are Key to Industry 4.0 Success
Companies are addressing Industry 4.0 skills gaps in their workforce and adopting more agile practices to mimic startups.