BigQuery Studio lets analytics practitioners use SQL, Python, Spark or natural language directly within BigQuery, to streamline analytics workflows.

The ability to process and analyze information in real-time is more than just an advantage—it’s a necessity. SAP HANA, with its in-memory technology, has emerged as a leader in this domain, offering businesses unparalleled speed and agility in data analytics. However, as powerful as SAP HANA is, maximizing its potential often requires seamless integration with other platforms and applications. Enter DreamFactory: an open-source API generation platform designed to connect the dots.

Advanced marketing analytics help you simplify multitouch attribution, create tailored marketing campaigns, and maximize return on investment (ROI) across channels. It helps you seek patterns and insights to improve marketing performance. These days, you can’t do online marketing without advanced analytics. Moreover, you need the right tools and skills to make sense of data scattered across multiple apps.

Today, we are thrilled to announce workers are generally available on Koyeb! You can now easily deploy high performance workers to process background jobs in all of our locations. It's now simple to deploy workers from a GitHub repository and rely on our built-in CI/CD engine: simply connect your repository and we build, deploy, and scale your workers on high-performance servers all around the world.

With millions of users and a 2023 evaluation of over $9 trillion, it’s time to dive into user payment testing with intent, strategy, and ferocity. These five best practices help identify and rectify common issues before causing severe problems in merchant systems. Errors in payment gateway functionality have enormous potential to derail the relationship between consumer and vendor. Customers expect seamless, functional transactions without confusing messages or complicated steps.

Ever had your live app crash after a new update, forcing you to spend your weekends fixing it? Let us guess, an enthusiastic developer introduced a change without testing it thoroughly. But it’s not just app development that can go rogue. Whether it's last-minute changes to client reports, tweaks to your marketing campaign, or any other update in a live setting, unexpected problems can crop up.

In the rapidly evolving business technology landscape, Enterprise Resource Planning (ERP) systems have emerged as essential tools for organizations looking to streamline operations, enhance efficiency, and elevate decision-making processes. An ERP system integrates various business processes, such as finance, human resources, sales, and inventory, into a unified platform, fostering cohesion and productivity.

Do you ever feel stuck following the same scripts and testing routines? Automated and manual regression testing can save time, but they often miss the more profound issues hidden beyond the happy paths. If you wish to bring more flexibility to your testing and take a more central spot in the testing process, consider including exploratory testing into your software testing life cycle (STCL).

In the digital age, data is the lifeblood of any organization. The way you store and analyze your data can significantly impact your success. This is where data warehouses come into the picture. Data warehouses are essential for businesses of all sizes, as they provide a central repository for data from a variety of sources, which can then be used for analysis and reporting. This data can be used to make better business decisions, improve operational efficiency, and identify new opportunities.

I’m calling it now. The next battleground for analytics adoption among business users will be the productivity suite. Let’s unpack that statement by considering these two examples: Traditional BI has always forced you down a one-way street for answers—drop what you are doing, login to the BI tool, and pray to the data deities that you can find the answer you’re looking for.