Hashing is a cornerstone of computer science, used extensively in data structures, cryptography, and distributed systems. Among various hashing algorithms, MurmurHash stands out for its speed, efficiency, and suitability for non-cryptographic applications. In this blog, we will delve into what MurmurHash is, when to use it, and how it compares to other hashing techniques, along with practical examples.

The world of software development is undergoing a huge transformation, due to the emergence of artificial intelligence (AI). AI-powered tools and methodologies are reshaping how we write, test, and deploy code, which is making our programming faster, more efficient, and more accessible. In this blog, we’ll explore the concept of code with AI, its applications, benefits, and its potential to redefine the future of technology. So, let’s dive in!

Snowflake combines unmatched scalability, performance, and ease of use. It simplifies the complexities of traditional data warehousing, enabling businesses to store and analyze data at scale without the overhead of infrastructure management. But to truly unlock the power of Snowflake, businesses need an efficient and secure way to move data into it.

Far too many small businesses, especially those without internal digital marketing teams or those working with external marketing professionals or agencies, overlook one of the most critical aspects of a well-rounded SEO program: data-driven SEO. According to a recent Databox research, 67% of businesses handle content marketing and SEO internally, yet many may not be fully leveraging data to optimize their efforts.

Over the past month, our primary focus has been on fixing bugs (you can check our Wiki for details on those), however, we do also have some new functionality to offer - the ability to apply labels not just to tests, but to test runs as well, as well as some other improvements.

Over the last decade, data has been hailed as the new oil, the new gold, the new currency, the new soil, and even the new oxygen. All these comparisons drive home the same point: data is important. If you’re running a business today, you need data for informed decision-making and strategy development. However, reliably extracting this data is a constant responsibility.

Black Friday is when eCommerce sites face their toughest critics: deal-hunting shoppers with zero patience for glitches. Were you aware that 47 of visitors anticipate a website to finish loading within 2 seconds? Even more concerning, half of the visitors will leave a sluggish website and switch to a competitor. One crash during busy times can lead to significant financial loss and permanent harm to your brand's image.

Business leaders are worried that despite their fervent enthusiasm for building innovative solutions, they haven’t been able to explore even half of the possibilities that digital has to offer. This anxiety has made CXOs desperate to associate with keywords like Generative AI, multi-cloud, SaaS, and more. However, accommodating these big technologies in a rush often comes at the cost of quality.

Today’s energy systems face a critical challenge: they often operate in isolation, with little real-time communication between key components like wind turbines and transformers. This lack of connectivity leaves gaps in performance optimization, predictive maintenance, and seamless grid management. With no existing technology robust enough to bridge these divides, the sector remains vulnerable to disruptions and inefficiencies.

AI is becoming a part of our everyday lives, and in the software testing industry, it is starting to show its impact as well. Traditional testing methods can often happen at a later stage of the development life cycle, which may present challenges for meeting the demands of modern software delivery. This is where shift-left testing comes to shine. This testing methodology has become one of the most used strategies for delivering high-quality software without missing bug findings along the way.