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Big Data Application

Big data applications are a growing requirement for businesses in a wide range of industries. Whether its real-time IoT analytics delivery to stakeholders or diagnostics for health care organizations, big data applications and technology in general have been growing 5 to 6 times higher than the overall IT market. 

Traditionally, big data application development and deployment have often been difficult endeavors. High data volumes, shaky ROI assumptions and ever changing requirements can make a big data project time consuming and resource intensive.

Given the amount of energy expended on data analysis in general, many businesses tend to stick to well-worn data hypotheses and do not take the time to explore new avenues, which rob them of the chance to uncover even more valuable information. Big data applications, done right, can help unlock new inisghts.

Snowflake for the Big Data Application

Snowflake's cloud data platform provides developers with the most modern infrastructure available to build, test, and deliver apps to stakeholders. With its near-zero management platform that instantly scales, data engineering and development resources can spend less time worrying about operational performance and more time building powerful new analytics tools.

Snowflake acts as a high-performance, low-latency analytics engine and big data platform that supports all data science workload requirements and integrates with Python, Spark, R, and other services. Its cloud architecture elastically supports any customer-facing analytics applications you want to build.

Read more:

eBook: How to Build Succcessful Data Applications on Snowflake

eBook: Three Tips for Building Modern Data Applications