Ukraine is a leading choice for IT outsourcing, thanks to its skilled talent and strong cultural alignment with Western clients. The country offers a deep pool of tech experts, a solid STEM (Science, Technology, Engineering, and Mathematics) foundation, and a thriving tech industry, making it a valuable option for businesses. When you work with Ukrainian firms, you get reliable software, smooth collaboration, and a shared drive for innovation.

Computational chemistry relies on large volumes of complex data in order to provide insights into new applications, whether it’s for electric vehicles or new battery development. With the emergence of generative AI (GenAI), the rapid, scalable processing of this data has become possible and critical to investigate previously unexplored areas in catalysis and materials science.

While data lakes make it easy to store and analyze a wide variety of data types, they can become data swamps without the proper documentation and governance. Until you solve the biggest data lake challenges — tackling exponential big data growth, costs, and management complexity — efficient and reliable data analytics will remain out of reach.

ERP providers constantly seek ways to enhance their offerings, streamline operations, and provide superior value to their clients in the ever-evolving landscape of enterprise software. One of the most transformative strategies in this domain is the integration of iPaaS (Integration Platform as a Service). This blog post explores how partnering with an iPaaS can significantly boost an ERP provider’s capabilities, offering strategic advantages and substantial ROI.

Reddit is a news aggregation, communication, and discussion application. If you want to get more information about a particular topic or have a question, Reddit is the place to be. The data on Reddit are provided to the public through both the website and its API. Learning how to use the Reddit API is beneficial if you want to integrate Reddit communications into your application or if you just want to use certain data on Reddit.

It’s a new world—again. Data today isn’t what it was five or ten years ago, because data volume is doubling every two years. So, how could ETL still be the same? In the early ‘90s, we started storing data in warehouses, and ETL was born out of a need to extract data from these warehouses, transform it as needed, and load it to the destination. This worked well enough for a time, and traditional ETL was able to cater to enterprise data needs efficiently.