In today’s data-driven world, understanding and leveraging customer data is essential for any business. CRM Analytics (CRMA), or Tableau CRM, is Salesforce's advanced analytics platform, enabling businesses to gain insights from their CRM data. It is designed for data analysts to dig deeper into customer data, generate actionable insights, and help drive business decisions.

From artificial intelligence (AI) to machine learning (ML) to conversational chatbots, the tools we use to interact with and consume information are rapidly changing thanks to powerful new technologies that make understanding our data more accessible than ever. One particularly influential field is natural language technology (NLT) and its branches.

The GenAI revolution is well and truly here. To take inspiration from our favorite comfort show, Gilmore Girls, “It’s GenAI’s world, and we’re just living in it.” In fact, McKinsey reports the number of organizations regularly using GenAI has doubled in ten months between their 2023 and 2024 surveys.

Managing issue tracking across teams can be straightforward with centralized platforms like GitHub or BitBucket. But what happens when your testing needs go beyond basic coordination?

Traffic replay is a valuable technique for capturing and analyzing network interactions, providing essential insights into user behavior and website performance. Utilizing existing traffic enhances software testing accuracy, allowing for more realistic application testing and ensuring that various environmental factors do not lead to unnoticed errors.

Machine learning operations (MLOps) is a practice that focuses on the operationalization of machine learning models. It involves automating and streamlining the lifecycle of ML models, from development and training to deployment and monitoring. Much like data operations (DataOps), MLOps aims to improve the speed and accuracy of the data you’re accessing and analyzing.

Imagine you need to explain the key differences between Test Plans and Test Strategies at a software developer’s meeting. You know there’s a distinction, but the details blur together. Don’t worry; you’re not alone. This post which includes some test plan examples, is designed to clear up the confusion surrounding these crucial documents, essential for understanding the framework of successful software testing.

Need groceries? Just order online. Want printouts on priority? Upload it online and get it delivered to your doorstep in no time. Looking for a cook? Well, there’s an app for that too! So, why should the pharmacy industry be left behind? That’s why the demand for pharmacy app development came into the picture. Reason?

Let’s be honest – AI can seem like a bit of a mystery, and with this mystery comes myths and misconceptions. Is it actually that good? Can it handle varying document structures? Can it integrate with my existing systems? Because of this mystery, many companies have yet to take the leap and incorporate AI into their data processes. Today, we’re going to play MythBusters, separate fact from fiction, and show how you can use AI document processing to maximize efficiency and save costs.