Running Spark Jobs with data in your Data Warehouse

Data Warehouse

Data warehouses are popular because they allow organizations to store large amounts of data from disparate sources in one place, making it easier to analyze and make decisions based on that data. Data warehouse software allows you to process, transform, and utilize data for decision-making. Data warehouses can provide a stable, centralized repository for large amounts of historical data. They can improve business processes and decision-making with actionable insights, and can increase a business's data strategy return on investment (ROI) and improve data quality.

Spark

Apache Spark is an open-source data processing engine that is designed to improve data-intensive applications' performance. It provides a more efficient way to process data, which can be used to speed up the execution of data-intensive tasks. It lets you process big data sets faster by splitting the work up into chunks and assigning those chunks across computational resources. Spark has been called a "general-purpose distributed data processing engine" and "a lightning-fast unified analytics engine for big data and machine learning". It provides development APIs in Java, Scala, Python, and R, and supports code reuse across multiple workloads, batch processing, interactive SQL queries, streaming analytics, machine learning, and graph processing. Spark is especially used to access and analyze social media profiles, call recordings, emails, etc. This helps companies make correct business decisions for target advertising, customer retention, fraud detection, etc.
With the growing popularity of both data warehouses for storage and Spark for compute workloads, it is unsurprising that many organizations are seeking to run Spark jobs with data in their data warehouse. Kaspian offers native connectors for the most popular data warehouses. Just register your data warehouse as a Datastore and link your Spark 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.

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