Data transformation involves altering, refining, and structuring information into a standardized and usable format. It plays a key role in enabling effective data analysis, supporting decision-making, and driving organizational growth. Read more about different types of data transformation, as well as its benefits and challenges.
In this article, we will compare two approaches to data processing, namely batch and stream processing. Each of them has different characteristics and serves different purposes, but we will attempt to break them down to help you decide which one would better suit your project.
Data is a critical asset that provides valuable insights into customer behavior, market trends, and operational efficiency. However, managing big data can be a challenge. Businesses that struggle to do so effectively may face increased costs and missed growth opportunities. One way to stay competitive and grow is through gradual engineering improvements.
Scala 3 gives you the tools to design the perfect Spark API. We proved it by creating the open-source library Iskra.
