Down to the Individual Grain: How John Deere Uses Industrial AI to Increase Crop Yields Through Precision Agriculture
Recently, The Verge spoke with Jahmy Hindman, CTO at John Deere, about the transformation of the company’s farm equipment over the last three decades from purely mechanical to, as Jahmy calls them, “mobile sensor suites that have computational capability.” This is in service to John Deere’s “smart industrial” strategy. More than just selling a piece...
Databricks Solutions Showcase
Inspiration doesn’t always come from our peers. Some of the best ideas come from innovators in other industries.This is especially true when it comes to data science and AI/ML innovations being applied to business processes and all aspects of operational decision-making. Consider fraud: Who knows how to analyze millions of data points in real-time better...
Jump Start Your Data Projects with Pre-Built Solution Accelerators
Deliver value faster. We hear this theme in nearly every executive discussion with customers. Data teams and data leaders need to deliver value in weeks, not months or years. The business climate is volatile, and they don’t have the luxury of long project timelines to deliver data and analytic capabilities designed to drive business value, such...
How to Secure Industrial IoT (And Why You Should Assume You Can’t Prevent a Data Breach)
The Industrial Internet of Things (IIoT) is already driving massive productivity gains in the Manufacturing and Energy & Utilities industries through decreased waste, automated quality control, predictive maintenance (increasing overall equipment effectiveness) and optimized energy consumption...just to name a few. At the same time, internet-enabled equipment and IoT devices present a cybersecurity vulnerability, particularly to...
Guide to Media & Entertainment Sessions at Data + AI Summit 2021
Data + AI Summit is the global event for the data community, where 100,000 practitioners, leaders and visionaries come together to engage in thought provoking dialogue and share the latest innovations in data and AI. At this year’s Data + AI Summit, we’re excited to announce a full agenda of sessions for data teams in...
Guide to Manufacturing & Distribution Sessions at Data + AI Summit 2021
Download our guide to Manufacturing at Data + AI Summit to help plan your Summit experience. Data + AI Summit is the global event for the data community, where 100,000 practitioners, leaders and visionaries come together to engage in thought-provoking discussions and dive into the latest innovations in data and AI. For those in...
Databricks Named Data Science & Analytics Launch Partner for New AWS for Media & Entertainment Initiative
“Digital transformation” isn’t just a buzzword – especially in the media and entertainment industry. More than just a more efficient way of creating or distributing content, the move to the cloud for media workflows is a necessity in order to meet high audience demands of “more content, right now” (while my kids can watch the...
Solution Accelerator: Telco Customer Churn Predictor
Skip directly to the notebooks referenced throughout this post. When T-Mobile embraced the un-carrier label, they didn’t just kick off a marketing campaign; they fundamentally changed the dynamics in the US market for telecom. Previously, telecom had been a staid, utility-like industry with steady growth and subscribers locked into two-year contracts to cover a “free”...
Learn How Disney+ Built Their Streaming Data Analytics Platform With Databricks and AWS to Improve the Customer Experience
https://youtu.be/WAOrqsHpJuM Martin Zapletal, Software Engineering Director at Disney+, is presenting at re:Invent 2020 with the session "How Disney+ uses fast data ubiquity to improve the customer experience". In this breakout session, Martin showcases Disney+’s architecture using Databricks on AWS for processing and analyzing millions of real-time streaming events. Abstract: Disney+ uses Amazon Kinesis to drive...
Delta vs. Lambda: Why Simplicity Trumps Complexity for Data Pipelines
“Everything should be as simple as it can be, but not simpler” - Albert Einstein Generally, a simple data architecture is preferable to a complex one. Code complexity increases points of failure, requires more compute to run jobs, adds latency, and increases the need for support. As a result, data pipeline performance degrades over time,...
