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5 Steps to Implementing a Data Literacy-Driven DataOps Framework
DataOps is a new framework that has been gathering greater attention in the past year since it first appeared on the Gartner Hype Cycle. DataOps is defined as a new way of thinking related to data which encompasses people, processes, and technology, resulting in improved collaboration and streamlined decision-making... Read more
How Can You Combine DevOps and Automation for Robust Security?
In this article, we will be taking a look at how the organizations can leverage the potential of DevOps and automation in order to evolve their business. As the engineering teams are trying to innovate at a quicker and... Read more
5 DevOps Challenges To Overcome To Gain Productivity
Editor’s Note: Is your business ready to implement DevOps? Learn more at ODSC West on how you can do just that. DevOps brought the development community to the agile era where multiple teams can work in a collaborative environment sharing their skills, knowledge and development responsibilities. As competition is increasing... Read more
5 Mistakes You’re Making With DataOps
Data is the driver for just about every modern business, and as companies consume more data more intelligently, there’s a need for a better community and higher buy-in. DataOps stands to do to data what DevOps did to development.   [Related Article: Data Ops: Running ML Models in Production... Read more
7 Steps to Go From Data Science to Data Ops
Not too long ago, data operation wasn’t on the radar, but now that it’s all people talk about, how can you move efficiently from data science to data ops? Gil Benghiat, co-founder of Data Kitchen, shares seven steps to do just that. [Related Article: The Difference Between Data Scientists... Read more
Data Ops: Running ML Models in Production the Right Way
Editor’s note: Check out Ido’s talk at ODSC East 2019 this May, “From Zero to Airflow: Bootstrapping Into a Best-in-Class Risk Analytics Platform.” The tipping point Many organizations reach the point in which new goals for SLA, scale, or efficiency simply exceed the capabilities of their existing data / ML... Read more
6 Reasons Why Data Science Projects Fail
In this article, I will dig deep into my years of experience as a tech journalist and practicing data scientist and reflect on numerous conversations I’ve had with companies about their data science projects in order to identify what I’ve seen as the top reasons why many projects fail.... Read more
The History of Big Data Processing in 5 Critical Papers
Read the History of Big Data Processing in These 5 Papers Big data is a multi-faceted area of interest and growth in today’s digital world. While many understand the core concepts of big data, the history is lesser known. Individuals interested in big data processing can brush up on... Read more
Sheddable Requests: The Intersection of Hackweeks, Book Clubs, and Site Reliability Engineering
One of the things I love about working at Civis is the opportunity we have for continuous learning. Not long ago I had the opportunity to be involved in a book club which read through Google’s Site Reliability Engineering book. One of the essays in this book addressed various methods for handling... Read more
Why You Should Hire a Chief AI Now
Artificial Intelligence is like Lego; to build something nice, you need to combine the right pieces in the right way. Most of us have played with Lego when we were small. I did at least and I absolutely loved it. I can remember the days when my friends and... Read more