Software Engineering Insights

Most software systems of contemporary large-scale businesses function at full capacity as they have to deal with complex computations across distributed system architectures. In these cases, system failures have a high likelihood with the cause of failure remaining largely elusive. Chaos engineering is a field that is finding widespread application as a reliable means to be prepared for such failures in advance.

Organizations irrespective of industry accumulate data across categories such as purchase history, customer contacts, lead journey statistics, buyer behavior, and so on. The most preferred mechanism to track and leverage this data today is through Customer Relationship Management (CRM) software such as Salesforce CRM. What makes Salesforce a highly viable CRM solution is the suite of low code application development tools it provides.

An organization’s data is its most essential resource and its day-to-day operations produce data in abundance. But to derive actionable insights that help make data-driven decisions, it is important to remove inefficiencies in the way the data is consumed and visualized. Business Intelligence, or BI, is a group of services that empower businesses to leverage their data for driving enterprise excellence.

Over the last half-decade, Artificial Intelligence solutions has made incredible advances in pivotal areas such as vision, video generation, linguistic processing, trend prediction, and so on. While AI attempts to make giant leaps toward matching human intelligence, industry insiders forecast the emergence of Artificial General Intelligence (AGI) as the next obvious step.

The global technology ecosystem has an insatiable demand for AI today but without the right training data and efficient AI model development, this domain cannot be utilized to its full potential. With fully actualized AI models that arise from high-quality build lifecycles, continuous innovation in AI fields such as Natural Language Processing (NLP) or predictive analytics can be ensured.

Taking a business to a global scale involves navigation, not just through untraversed markets but also across language-based hurdles. Natural Language Processing (NLP) offers the utility of Machine Translation, wherein a source language is converted to a target language automatically with significant accuracy. It is the most viable solution to a fast and effective translation process without human intervention.

Every business needs to continuously find ways to utilize a workday to make the most of it. So, workflow automation in various business areas is the go-to alternative for a lot of enterprises. The Customer Relationship Management (CRM) workflow for businesses, handled by marketers, customer service executives, and sales reps, also derives cost and time efficiency-related benefits from automation.

In today's advanced competitive world, the most valuable commodity is data. Data has many forms, from pictures of people and places to patient records and banking transactions. Machine Learning is a branch of Artificial Intelligence that can fully leverage this data to learn from it and enhance a business' bottom line.

The software development and delivery pipeline of DevOps, also referred to as the CI/CD pipeline, ensures that market-ready software products are released for public use faster. Continuous Testing is a set of evaluation procedures in the DevOps pipeline meant to ensure the product's quality and to enhance the reliability of the outcome.

Today, we are at a point in the software delivery paradigm where most IT enterprises have implemented DevOps in their workflow in some way, shape, or form. DevOps teams are guided by various operating principles, the most prominent of which are Continuous Integration (CI) and Continuous Delivery (CD), or CI/CD.