Articles

In the ever-changing digital landscape, the evolution of Digital Native Businesses (DNBs) is not just a trend but a necessity. As businesses scale, their technology platforms must evolve to meet the demands of an increasingly competitive and digitally savvy market. Let’s delve into the transformation journey of DNBs and explore the critical aspects they need… Continue reading Evolving Digital Landscapes: Scaling Digital Native Businesses for Success

Explore the best practices for designing and implementing a multitenant SaaS architecture to enhance scalability, efficiency, and cost-effectiveness. Tenancy Models Tenancy models in a multitenant SaaS architecture refer to the different ways in which tenants are organized and managed. There are several common tenancy models, including: Shared Database – In this model, multiple tenants share… Continue reading Best Practices for Multitenant SaaS Architecture

Early cloud adoption was driven by advantages of operating expenditure (OpEx) over capital expenditure (CapEx) and outsourcing advantage of infrastructure & infrastructure management. Platform & infrastructure services spending contributed majorly into cloud spending for enterprises.

Unleashing Generative AI’s Potential for Positive Change in Business. Let’s dive into the transformative journey of integrating #GenerativeAI.

Java thread dumps: Analyzing performance bottlenecks and concurrency issues

Boost productivity through collaborative power of Microsoft Teams apps

You would hear a lot about the three V’s of data – Volume, Variety & Velocity. Every enterprise and almost any application of enterprise grade is facing growth in consumption and therefore, growth in the data it consumes, generates, processes & stores as well as the forms of the data that’s been processed.

Fueled by advancements and breakthroughs in Computer Vision, it is now possible to visualize, detect and track anything in real-time. Enormous amounts of images are fed into deep learning architecture, which was inspired by the human brain, in order to comprehend the features of a subject. It requires a significant amount of computation to extract features from such a large collection of images and videos.

We are all familiar with CAPTCHA — acronym for “Completely Automated Public Turing test to tell Computers and Humans Apart”. A CAPTCHA test is designed to determine if an online user is really a human and not a bot. Through Captcha, the user is asked to perform a certain task, such as enter the text written in the image or click on the images from a set of different images that match the required criteria. CAPTCHA helps protect you from spam and password decryption by asking you to complete a simple test that proves you are human and not a computer trying to break into a password protected account.

NoSQL database offer great power to developers and organizations in form of fluidity of data definition and data structure. However like any other transition, moving from relational databases to NoSQL also requires a mindset shift and if you do not stop thinking relational, you may land in more problems than the one you are trying to solve by using NoSQL. This post tries to provide some pointers to catalyze such transition.

The evolution of development tools has also led to the evolution of testing tools too, thus supporting and firming up the entire process of Quality Assurance. One among them is automation testing, talking about which it may be difficult to ignore the popular, open-source tool – Selenium. With changing times, the automation tools are also changing at a rapid pace. There are plenty of automation tools today that can be used as a fragment of your automation process. This article centers on the most promising and featured filled tool, Cypress.

In Supervised Machine Learning, we do either ‘Estimation of a Value’ OR ‘Classification into a category’. Naturally, the predicted variable values are then Numerical or Categorical respectively. Here in this BLOG we explore how in peculiar cases, can both of them might be tried basis final expectation from the Salesforce Einstein prediction model.