Business Over Broadway

FEBRUARY 19, 2019

Data science projects require data professionals to devote their energy toward different activities toward project completion. Results of a recent study of over 23,000 data professionals found that data scientists spend about 40% of gathering and cleaning data, 20% of their time building and selecting models and 11% of their time finding insights and communicating them to stakesholders.

Data Science 109

Data Science Statistics Modeling Visualization 109

DataRobot

FEBRUARY 19, 2019

You’ve decided: DataRobot is cool. You saw a demo. Your people tell you they like it. You like the way it makes data scientists more productive. And you love the way it helps you introduce new people to machine learning.

Machine Learning 75

Machine Learning IT Data Science 75

Dataiku

FEBRUARY 19, 2019

POCs often feel like a gamble. You're testing the boundaries of your business's technological capacity and your ability to change at the same time. If your POC is an anomaly or you're unprepared to activate it, you risk missing out on technology that could keep your business on top. The choice for a data specific POC is critical, because organizational resistance to change is one of the biggest barriers to data integration.

Testing 49

Testing Data Integration Risk Technology 49

Teradata

FEBRUARY 19, 2019

Rob Armstrong explains that while data is important, the real key is preserving the relationships across the data models that leads to insight and successful business outcomes.

IT 40

IT Modeling 40

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Experimentation

Smarten

FEBRUARY 19, 2019

What is Smart Data Visualization? Smart data visualization is a crucial part of advanced analytics. Smart visualization allows business users to view and analyze data to identify a problem, clarify a root cause, identify a business opportunity, and to make confident decisions. Business users can interact easily with visual analytics tools to build a view that will tell a compelling story using guided visualization tools so there is no need for assistance from data scientists or delay in finding,

Visualization 40

Visualization Machine Learning Interactive Analytics 40

Nutanix

FEBRUARY 19, 2019

In case you missed it (wink), we launched our global You Decide campaign last month. Over the course of 3 blogs, I’ll dive in deeper to what it means to say goodbye to painful upgrades, true up surprises, vendor lock in and fire drills.

IT 20

IT 20

3AG Systems

FEBRUARY 19, 2019

Mining operations are complex environments. Even for something as “simple” as surface mining or open pit mining, there are a whole host of variables to consider. Small changes in blasting operations, haul truck speed, stockpiling, and equipment can have significant impact on throughput and operating cost. Furthermore, all these components are inter-related, making second-order effects difficult to identify, let alone correct.

Data Processing 40

Data Processing Analytics Optimization 40