Systems | Development | Analytics | API | Testing

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Understanding IT Infrastructure Residency Services and Their Value

As technology evolves, the skills gap within IT departments continues to widen. New technologies are being adopted more quickly to keep pace with business changes, necessitating a constant update of skills. Yet, fully outsourcing these skills isn’t always the solution, as they are a core part of any IT organization. To effectively address this issue, we need a strategy that focuses on continually closing the skills gap.

Insurance Claims Process Automation: 3 Areas to Automate

In the insurance industry, the claims process can often feel like a complex maze of manual processes for both customers and agents. However, new and advanced technologies are paving the way for smoother, more efficient claims handling. Claims processing automation at insurance companies can streamline routine tasks, reduce risk of errors, and enhance customer satisfaction. In this blog, we’ll explore three key areas to focus on for effective automation.

What is natural language search (NLS)?

Business leaders find themselves involved in a range of high-priority tasks, most of which require making critical decisions. Let’s say you’re the sales head of a global organization. You’re ready to make an important decision about next quarter’s sales strategy, but you must first look at the right data set. You know it exists somewhere in your organization’s databases, yet it’s not within the arm’s reach.

An Overview of Pull Request Processes in Testing

One method that developers use to submit code modifications for evaluation is known as pull requests (PRs). We discussed the advantages of testing PRs in software development in a previous post but before merging into the main branch, they give team members a chance to talk about the changes, make suggestions, and accept or reject the code. To keep code quality high and make sure that the team reviews all changes, this approach is essential.

Exploring Salesforce Data Cloud: A Comprehensive Guide for Data Analysts

The Salesforce Data Cloud is a powerful tool that enables businesses to collect, unify, and analyze customer data from multiple sources in real time. As data analysts, the Salesforce Data Cloud provides numerous opportunities for deep insights, better decision-making, and delivering personalized customer experiences.

A Comprehensive Guide on CRM Analytics for Data Analysts

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.

Transforming the way you pay for realtime - by the minute!

Our new per-minute, consumption-based pricing model offers granular control over your costs, eliminating the need to pay for peak users or connections. Whether you're building a proof of concept or handling massive user loads, our pricing model provides what you need to succeed - volume discounts, cost optimizations and business critical support. Consumption-based pricing has become widespread in SaaS and PaaS businesses, and it's easy to understand why: you should only ever pay for what you consume.

What Is Regression Testing in Agile? Concept, Challenges, and Best Practices

Imagine your development team just rolled out a new feature that fixes a bug but now some parts of your software that used to work flawlessly have stopped working. This is a common risk in Agile development, where changes come fast and often. Since Agile moves quickly with constant updates, regression testing is a key part of making sure the software stays reliable. With each new update, there’s a risk that changes might impact parts of the software that were already working well.

Automated Financial Document Processing: Your Path to Becoming a Success Story

The financial document processing domain has undergone a 360-degree shift in the past decade. It was at the brink of the 1980s when software providers began releasing document management systems aimed at helping companies save time, money, and effort in regard to financial document processing. What started as simple document management systems using Optical Character Recognition to digitize printed financial documents has evolved into advanced, AI-powered solutions.