Tag: Data Scientists
How to Manage ML Workflows Like a Netflix Data Scientist
Data scientists want to do data science. It’s right there in the title, after all. But data scientists often are asked to do other things besides building machine learning models, such as creating data pipelines and pr Read more…
In Search of the Data Dream Team
When it comes to succeeding at big data, the people you put in place are just as important--if not more important--than the products and technologies you use. One of the folks exploring the intersection of people and dat Read more…
And the 100 Fastest Growing AI Teams Are….
Investments in AI are growing quickly at the moment, as the combination of big data and advanced data science techniques work their way into every industry on the planet. But which companies have the fastest growing AI t Read more…
Big Data Study Cites Challenges, Predicts Growth
Tapping into big data analytics continues to be appealing for many companies who wish to mine their data for “actionable insights,” or information that can assist decision makers with bringing increased value to thei Read more…
ML Needs Separate Dev and Ops Teams, Datatron Says
In the machine learning world, the folks developing models often are the same folks who are tasked with running the models in production. And they often use the same end-to-end ML software stacks. But emerging best pract Read more…
Why Data Scientists and ML Engineers Shouldn’t Worry About the Rise of AutoML
Low-code and no-code development tools are becoming increasingly popular, and the pandemic only accelerated this trend. When we think of low-code or no-code development, we’re usually referring to tools that allow a no Read more…
Why Data Science Is Still a Top Job
This year, for the first time since 2016, data scientist is not the number one job in America, according to Glassdoor’s annual ranking. While the shine may be wearing off the unicorn a bit, data science is still a grea Read more…
Is Kubernetes Really Necessary for Data Science?
It seems almost preordained at this point: Thou Shalt Run Thy Data Science Environment On a Cloud-Native Kubernetes Platform. This is 2020, after all. How else could it possibly run? But Tyler Whitehouse, a data scientis Read more…
Kepler AutoML Targets Next-Gen Business Analysts
As more companies roll out digital infrastructure, they are ingesting greater volumes of data that can be used by business analysts to gauge customer intent and boost transactions. Complexity and lack of data scientists Read more…
COVID-19 Gives AI a Reality Check
While it seems unlikely that AI will enter another nuclear winter, the current COVID-19 situation is giving enterprises the opportunity to rethink their AI strategies, giving the better AI projects more room to run, whil Read more…
2019: A Big Data Year in Review – Part One
At the beginning of the year, we set out 10 big data trends to watch in 2019. We correctly called some of what unfolded, including a renewed focus on data management and continued rise of Kubernetes (that wasn’t hard t Read more…
Dogged Determination: How Trupanion Pulled AI Across the Finish Line
David Jaw had reason to be excited. As a data scientist at Trupanion, Jaw had just put the finishing touches on the prototype of a machine learning model that could replicate the actions of a human claims adjuster with a Read more…
Restive Data Workers Head for Exits
In a sign of the growing bargaining power of “data workers,” one third responding to a recent survey said they would quit over what they considered an “unfair” performance review. Moreover, the survey released Read more…
Giving DevOps Teeth To Crunch Down on AI Ethics Governance
AI ethics is definitely trending. I’ve seen the phrase in my reading and heard it trip from the tongues of professional acquaintances many times in the past several months. Management fads come and go, and I wonder Read more…
‘Data Workers’ Failing to Cope
More evidence is emerging that “data workers” in general and data scientists in particular are bogged down by the sheer breadth of their company’s data. Meanwhile, the skills gap between data experts and line-of Read more…
BI Leader Sisense Acquires Periscope Data
Sisense’s acquisition of Periscope Data combines the buyer’s business intelligence platform with Periscope’s cloud data analytics expertise as Sisense looks to up its analytics game. The merger announced on Tues Read more…
AI Hype Rockets, Hadoop Twins, and Other Learnings from Strata
Strange similarities have been discovered to exist between Cloudera and Hortonworks now that the two former Hadoop rivals have merged into a single company. In fact, the resemblances are so great that they appear to be l Read more…
How To Find and Hire Data Scientists
So you're building a data science team. That's great news! As a business leader, finding a qualified data scientists is a critical step in your company's ability to harness big data and machine learning technologies, whi Read more…
The Hard Questions of Hiring For Machine Learning
I’ve been thinking a lot about hiring for the machine learning specialization lately. It’s no surprise. New data is emerging almost daily about the rise of machine learning, artificial intelligence and deep learning Read more…
Empowering Citizen Data Science
Companies of all stripes are turning to data science to unlock the value in their data. However, finding highly trained data scientists to build the systems has proven to be a very difficult task. Now many organizations Read more…
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