Systems | Development | Analytics | API | Testing

MLOps World Toronto: MLOps Beyond Training Simplifying and Automating the Operational Pipeline

Most data science teams start with building AI models and only think about operationalization later. But taking a production-first approach and automating components is the key to generating measurable ROI for the business. In this talk, Iguazio’s co-founder and CTO, Yaron Haviv, explains how to simplify and automate your production pipeline to bring data science to production faster and more efficiently. He displays real live use cases while going through all the different steps in the process.

Demo - Exploiting a data fabric to drive data literacy and data democratisation

Join Talend experts to learn how to drive data literacy and adoption throughout your organisation with a seamless data fabric. Discover how to balance collaboration, ease of use and governance to deliver trusted data insights and outcomes at the speed of the business.

A better way to import files and look at Linx

Building a file importer is not hard, but what if you can do it in an extremely short time. In this video, we build a file importer that reads a CSV file and makes the data available via REST API using the new Linx designer. Linx is a low-code development tool built for developers. Linx is a general-purpose platform that has no limitations on the technology it can connect to and uses visual abstractions of programming concepts to make building powerful and complex logic easy and maintainable.

How To Create Global Sample Rate Rules | Dynamic Sampling | Moesif in 100 Seconds

Dynamic sampling enables you to control which API calls are logged to Moesif based on customer or API behavior. This video will show you how to create sampling rules that apply globally across Moesif. Dynamic sampling is a fantastic cost-savings feature available to customers on our Enterprise plan. Moesif will intelligently extrapolate metrics for accurate reporting even with multiple sample rates in place. That means that no matter what rules or sample rates you have set up you can be sure you are still seeing an accurate representation of your data.

Differences between the C++ and Java MiNiFi agents

In this video we will go through all the differences between the C++ and Java MiNiFi agents. The video shows the differences observed on the Edge Flow Manager UI ranging from different information to the presence of buttons and dropdown elements determined by the agent type. Differences in feature set and functionality are also highlighted. The two implementations also have different footprints (memory and CPU) as well as a different set of available components. This video will help you determine the MiNiFi agent that best suits your use case.

The Chief Data Officer | Digital Transformation

Today, data isn't a cost center. It's a business driver. And Chief Data Officers are responsible for using data to create real results and transform their business. Meet Ray, the CDO at a high tech global electronics manufacturer. Ray relies on the Cloudera Data Platform to bring multiple data sources together, Ray's company can connect supply chain, go-to-market and product research data in one place, while lowering the cost on their network.