Running R Jobs with GCP GCS Data

GCP GCS

A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data, and run different types of analytics. Google Cloud Storage (GCS) is a popular object storage service that can be used as a data lake. It provides a simple and cost-effective way to store, manage, and analyze large amounts of data. GCS is designed for very high durability and availability.

R

R is a programming language that was created for statistical computing and graphics. It has become increasingly popular over the years because of its flexibility, ease of use, and powerful data analysis capabilities. R has a rich ecosystem with complex data models and elegant tools for data reporting. It offers a wide variety of statistics-related libraries and provides a favorable environment for statistical computing and design. R is especially popular among data scientists, statisticians, and researchers who work with large datasets. It is used for data analysis, statistical inference, machine learning algorithms, and data visualization. R can also be used for creating reproducible, high-quality research reports.

With the growing popularity of both GCP GCS for data storage and R for compute workloads, it is unsurprising that many organizations are seeking to run R jobs with GCP GCS data. Kaspian offers a native connector for this operation. Just register your GCP GCS datastore and link your R job; Kaspian's autoscaling compute layer makes it easy to crunch through any data in your cloud with minimal setup or management.

Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.