With data coming from so many different sources nowadays (both old and new, both internal and external), it is inevitable that data will arrive in many different structures, schema, and formats, with other variables for latency, concurrency, and requirements for storage and processing. When data types are extremely diverse and combined, we now call it “hybrid data.” This usually drives users to deploy many types of databases and different platforms to capture, store, process, and analyze the data, which in turn results in hybrid data management architectures.
cnvrg.io is used across industries to help enterprises accelerate AI from research to production by simplifying DevOps and dependencies involved in building production-ready ML.
Whether you’ve just begun the free trial, you’re a new user, or you’re interested in looking deeper into cnvrg.io features, we invite you to join us in a live workshop on how to get started using cnvrg.io.
To ensure that the third-party verification activities undertaken by companies are broadly comparable, CDP requires verification to be completed in accordance with recognised verification standards.
In this webinar, gold CDP-accredited solution provider, Greenstone outlines 5 key software tools for preparing your CDP data for verification.
McKnight Consulting Group
Whether to take data ingestion cycles off the ETL tool and the Data Warehouse or to facilitate competitive Data Science and building algorithms in the organization, the Data Lake a place for unmodeled and vast data will be provisioned widely in 2019. Though it doesn’t have to be complicated, the Data Lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the Data Swamp, but not the Data Lake! The tool ecosystem is building up around the Data Lake and soon many will have a robust Lake and Data Warehouse. We will discuss policy to keep them straight, send “horses to courses,” and keep up users’ confidence in the Data Platforms.