With the proliferation of cloud native applications, organizations today are dealing with an abundance of data from various sources. Collecting and analyzing this data effectively has become crucial for businesses to gain insights and make data-driven decisions. In this blog post, we will explore the best practices for data collection and analysis in the age of numerous cloud native applications, and how Crest Data Systems’ solutions can help organizations optimize their data strategies in this evolving landscape.
API-based integrations are widely adopted across many industries. They enable direct access to data and customizable data collection based on the requirement, however they do have maintenance overhead as the API’s can change over time. Alternatively, organizations can consider using a more abstracted solution for data collection and analysis in cloud native applications. This involves using a unified data pipeline and observability platform that provide a scalable and flexible approach to collecting and transforming data from various sources to different destinations for analysis.
Effective data collection and analysis are crucial for organizations leveraging cloud native applications to derive insights and make informed decisions. By following the best practices discussed in this blog post and leveraging Crest Data Systems’ solutions, organizations can ensure that their custom data collection and analysis efforts are optimized for accuracy, reliability, and meaningful insights, leading to improved business outcomes and competitive advantage in the cloud native landscape.