The misconception that product led growth implies a business neglects sales couldn’t be further from the truth. In reality, product led growth (PLG) involves integrating sales later in the customer journey, placing the purchasing power back in the hands of your users. This self-service approach is highly effective, especially when paired with insightful user data to streamline and target growth. For AI-centric companies, this product-led strategy serves as a fundamental pillar for success.

Recently we introduced one breaking change in how user information is exported from Countly, and we wanted to explain why such change was made and what to do to keep your plugins supported. But before we dive into why's, let's first reiterate the "what" part.

Data integration is essential for any competitive business. The ability to sync all your data from disparate sources powers better insights, analysis, and ultimately faster business decision-making. Change data capture (CDC) is one element of data integration that focuses on keeping data accurate with near real-time updates as soon as data within a data source changes.

As software testers, we are not just cogs in a machine, executing tests, writing reports, and meeting deadlines. We are professionals who can make a difference in the world. We can find purpose in our testing and use it as a guiding light through the challenges we face. Kristel Kruustük, the founder of Testlio, is living proof that finding a bigger sense of meaning and purpose can transform not only our work but also our lives.

Microsoft SQL is a popular relational database management system organizations use to manage and store data. As data volumes grow, extracting, transforming, and loading data has become essential for many businesses.

Like peanut butter and jelly, ETL and data modeling are a winning combo. Data modeling can't exist without ETL, and ETL can't exist with data modeling. Not if you want to model data properly. Combining the two defines the rules for data transformations and preps data for big data analytics. In the age of big data, businesses can learn more than ever about their customers, identify new product opportunities, and so on.

Commercializing an AI-based product requires turning technology into a marketable product, navigating challenges from development to market entry. Appealing to enterprise buyers is crucial for sustainable, continuous growth, as their interest not only validates your product’s value but also lays the foundation for long-term success and scalability. More specifically, the larger the businesses of your potential customers are, the more of a monopoly your product likely has in the market.

When monetizing APIs, specific ways exist to entice customers to begin using your services. Much of the time, users like to see some value before they commit to becoming a full-blown paid customer. One of the most popular billing providers we see used for API monetization is Stripe, and thankfully, Stripe supports free trial models. Paired with Moesif, you can easily adhere to what model you require to support your API monetization needs.

Ah, the sweet allure of a well-rested application. No, I’m not talking about kicking back and letting your software take a nap. I’m diving deep into C# and its Sleep method. Have you ever wondered, “Is there a Sleep function in C#?” We’ve got answers. By the end of this post, you’ll know all about the ins, outs and potential pitfalls of using Sleep in C#. So, grab your favorite beverage, and let’s get into it!