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Latest Blogs

Buy Your Embedded Analytics and Empower Your End-Users With the Right Data

The value of embedded analytics is unmistakable. Application teams that embed dashboards and reports drive revenue, reduce customer churn, and differentiate their software from the competition. While embedded dashboards create real value, they can also come with real costs. These costs are not always visible when companies plan for their analytics offering but can significantly impact production, scale, and the speed of bringing analytics to market.

Requirement Gathering Blog Series, Part 2: Requirements in the Agile World

This is Part 2 of the Requirement Gathering Blog series by Rahul Parwal. We’d like to thank him for sharing his expertise with the community through this information-packed piece. In the Agile methodology, the requirement-gathering “phase” is not as rigid and formal as in the traditional Waterfall method.

What Are the Different Types of Python Errors? - and How to Handle Them

There are several types of errors that can occur in Python. Each type indicates a different kind of problem in the code, and comprehending these error types is crucial in creating effective Python applications. The most common types of errors you'll encounter in Python are syntax errors, runtime errors, logical errors, name errors, type errors, index errors, and attribute errors. Let's go through each with examples.

The Power of Superapps: How Composable Apps Are Transforming Mobile App Development

Superapps take the features and functions of several apps to create a single powerful app that allows users to accomplish multiple tasks in one place. With mobile app users spending more time on apps each day, what are the benefits of creating a superapp for companies?

AI Center of Excellence: 6 Tips for Success

Artificial intelligence (AI) has become increasingly important as organizations use it to drive innovation, enhance efficiency, improve decision making, and boost digital transformation efforts. But ensuring success requires significant, ongoing efforts. Consider setting up an AI center of excellence (CoE) to boost the success of your AI initiatives.