Systems | Development | Analytics | API | Testing

How Sense Uses Iguazio as a Key Component of Their ML Stack

Sense is a talent engagement platform that improves recruitment processes with automation, AI and personalization. Since AI is a central pillar of their value offering, Sense has invested heavily in a robust engineering organization, including a large number of data and data science professionals. This includes a data team, an analytics team, DevOps, AI/ML, and a data science team. The AI/Ml team is made up of ML engineers, data scientists and backend product engineers.

Data Replication Tools: Ensuring Data Consistency Across Systems

Today’s businesses generate more data than ever before. You need that data to be consistent and reliably accessible across disparate systems. But how? Here are five key takeaways concerning data replication tools: With multiple databases, applications, platforms, and other tools constantly generating data, it can be a challenge to maintain consistency and accessibility. Even the slightest error can mean unhappy customers, unreliable reports, failed analytics, and compliance issues.

Tricentis qTest awarded 3 TrustRadius 2023 Best of Awards

We are delighted to announce that Tricentis qTest has won three prestigious TrustRadius Best of Awards! TrustRadius is an unbiased, trusted B2B technology decisioning platform that offers vetted reviews by real users to help technology buyers make confident purchasing decisions. Best of Awards are based entirely on customer reviews, and serve to spotlight products with superior customer satisfaction.

Transforming SAP testing: Addressing key challenges with LiveCompare 2023.3

SAP testing is full of challenges, from complex migration processes to inefficient testing strategies. Tricentis LiveCompare mitigates these challenges by providing SAP teams with AI-powered analytics and insights that significantly reduce the risk, time, and cost of delivering and supporting changes to SAP solutions. LiveCompare’s latest release offers new enhancements to help our customers overcome these obstacles.

How #ChatGPT Acquires Its Knowledge? | Raju Kandaswamy | #SoftwareTesting #GenerativeAI

In this intriguing video, Raju Kandaswamy delves into the fascinating world of ChatGPT, unraveling the mechanisms behind how this powerful language model acquires its knowledge. Gain insights into the training process, the vast datasets involved, and the continuous learning loop that refines ChatGPT's language capabilities. Whether you're a curious user or a tech enthusiast, this session offers a behind-the-scenes look at the knowledge acquisition journey of ChatGPT, shedding light on the technology that powers its diverse and contextually rich responses.

Real-Time Example of APIs of a Leading Travel Company | Sidharth Shukla | #apitesting #api

Join Sidharth Shukla in this session as he provides a real-time exploration of APIs from a leading travel company. In this hands-on demonstration, Sidharth walks you through practical examples, showcasing the architecture, functionalities, and integration possibilities of APIs within the travel domain. Whether you're a developer, tester, or someone keen on understanding the intricacies of API usage in the travel industry, this video offers valuable insights and a firsthand look at the dynamics of APIs in a real-world scenario.

Ask Me Anything About Styling and White Labeling Yellowfin

Yellowfin makes it possible to combine action-based dashboards, automated data discovery, and data storytelling into a single, integrated, seamless platform — right in your user’s core workflow. Learn how to best to leverage these capabilities, starting with a walkthrough of the basics of white labeling Yellowfin along with some tips and tricks.

How HR Tech Company Sense Scaled their ML Operations using Iguazio

Sense is a talent engagement company whose platform improves the recruitment processes with automation, AI and personalization. Since AI is a central pillar of their value offering, Sense has invested heavily in a robust engineering organization including a large number of data and AI professionals. This includes a data team, an analytics team, DevOps, AI/ML, and a data science team. The AI/Ml team is made up of ML engineers, data scientists and backend product engineers.