Systems | Development | Analytics | API | Testing

Business Monitoring with ThoughtSpot

Business monitoring is essential to a company’s success. Whether you’re improving efficiency, saving costs, planning inventory, or tracking goals, you need to define metrics and monitor them regularly to make progress. With ThoughtSpot, business monitoring is an intuitive experience that starts with visualizing your KPIs in real-time so you can take action when there’s movement.

Deploying Your Hugging Face Models to Production at Scale with MLRun

Hugging Face is a popular model repository that provides simplified tools for building, training and deploying ML models. The growing adoption of Hugging Face usage among data professionals, alongside the increasing global need to become more efficient and sustainable when developing and deploying ML models, make Hugging Face an important technology and platform to learn and master.

Kong Named Leader in Gartner Magic Quadrant for Full Life Cycle API Management for Third Year

For the third consecutive year, we’re happy to announce that Kong has been recognized as a Leader in the Gartner Magic Quadrant for Full Life Cycle API Management and is positioned furthest to the right for Completeness of Vision. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document.

3 Features Developers Will Appreciate in the Appian 22.4 Release

The 22.4 release ends the year on a high note with faster Appian Portal deployment (via the Appian Designer), a stylish rebrand of the Appian Process Modeler (to keep your workflow looking good), and a time-saving automation upgrade (of the RPA agent launch process). With the last release of 2022, we want to say a special thank you to our dedicated Community of developers and engineers. Your expertise, feedback, and dedication to Appian are what keep us improving and expanding with every feature.

No-code/low-code cloud data mapping with Talend

Mapping source columns with a data destination is arduous and time-consuming. Data fields can come from many source types and formats. Even though you are the expert on your datasets, you may require the assistance of IT to set up the mapping. However, the more sources, the more handoffs, the higher the possibility of errors. As organizational data has become more dispersed and voluminous across organizations and applications, it's more important than ever to ensure that you understand your data.

The 7 Costly and Complex Challenges of Big Data Analytics

re:Invent 2022 is just around the corner and we couldn’t be more excited to share the latest ChaosSearch innovations and capabilities with our current and future customers in the AWS ecosystem. Enterprise DevOps teams, SREs, and data engineers everywhere are struggling to navigate the growing costs and complexity of big data analytics, particularly when it comes to operational data.

How Embedded Systems Impact Everyday Life

Embedded systems are at the core of various products, machinery, and intelligent operations like machine learning and Artificial Intelligence (AI). Since embedded devices are used in almost every industry today, embedded systems play a crucial role in the functioning of devices and machines we use daily, from vehicles to home appliances and medical devices. To further understand this, here's how embedded systems impact everyday life.

Once Upon a Time in the Land of Data

I recently had the privilege of attending the CDAO event in Boston hosted by Corinium. Tracks represented financial services, insurance, retail and consumer packaged goods, and healthcare. Overall, it struck me that while data science is not new, most firms are still defining the mission of the data office and data officer. It’s clear firms seek to leverage data and embrace its potential insights, but most are forging ahead in largely uncharted territory.