Software Engineering Insights

Businesses can save plenty of time and millions of dollars when they use data science to better understand and improve their processes. With the age of the democratization of data, there have been several emerging trends defining enterprise data manipulation and data engineering.  

Artificial Intelligence (AI) and data engineering are closely interlinked. On one hand, making sense of unstructured data is the process known as data science or data engineering. On the other side of the same coin, AI-programmed computers have the ability to learn as they go, getting better at solving particular sorts of problems as they accumulate more data. So one cannot exist without the other.

Speech recognition is a technology that has been going through continuous innovation and improvements for almost half a century. It has led to several successful use cases in the form of voice assistants such as Alexa, Siri, etc., voice biometrics, official transcription software, and the list goes on. So what really is Automatic Speech Recognition and what are the underlying technologies that enable it?

The business landscape of the modern world is heavily customer-centric with marketing, sales, and customer support at the center of operations. Salesforce is the most sought-after Customer Relationship Management (CRM) software intended for these purposes. There are a variety of roles and responsibilities in an enterprise's Salesforce team and the Salesforce Administrator is usually at the helm of it.

Increasingly today, Financial Technology (FinTech) companies have been using mobile devices and applications as promotional platforms. Biometrics technologies are a necessary addition to the FinTech domain and have the critical task of enhancing security through the accurate identification and verification of the customer's identity.

A majority of healthcare data today, about 80% of it, happens to be unstructured. Most sources used for aggregating Electronic Health Records (EHR) require a considerable amount of pre-processing because most of them are not machine-readable. Natural Language Processing (NLP) and various Machine Learning (ML) techniques can, however, unlock all the potential enmeshed in unstructured data.

When it comes to seeking app-based medical solutions, physical health is often given precedence over cognitive or mental health. However, millions of people suffer silently from unseen, yet debilitating effects of mental illnesses. That is the pain area that the creators of the research-backed mental wellness app Wysa have chosen to address. 

Post-pandemic, the retail sector has witnessed several transformations in the way it works, but the biggest paradigm shift has been the increased adoption of self-checkout systems. These systems give retailers the option of saving costs while enhancing the customer experience so that in-store resources can be better allocated.

Innovative medical interventions that are new to the healthcare industry need to be evaluated through clinical trials before they are rolled out for real-time implementation. The field of clinical trials is going through a paradigm shift with digitalization. And electronic Trial Master File (eTMF) systems are a clinical trial documentation necessity for digitalization.

Organizations whose bottom line depends on quality software development need a robust methodology in place to assure bug-free product delivery for their clients. They must integrate a means to monitor the productivity and quality of software testing with a standard set of appropriate software testing metrics.