Dataworkz Delivers No-Code Customer 360 With Couchbase Cloud

Customer 360 is one of the most popular use cases for Couchbase. However, a significant amount of effort is needed to collect data from disparate sources and then stitch it together to create the golden record. While the extract, transform, and load (ETL) process is a popular way to integrate data from multiple sources, it doesn’t take advantage of the flexibility NoSQL databases offer. Instead, extract, load, and transform (ELT) is much better suited to the schema-free world of NoSQL, as it removes the need to get data into a standardized format. ELT was created to address the three Vs of big data – velocity, volume and variety – which pushed the capacity, resources, cost, and timeliness of traditional ETL to the breaking point. Today’s ELT does a great job at E and L but doesn’t really solve the problem of T. The challenge for ELT is to incorporate data governance and data collaboration to effectively address the fourth V in big data: veracity. EL+T addressed the above challenges. Architecturally, you can think of “+T” as an integrated data governance, transformation, and collaboration hub, unifying all of these features into a seamless, visual, easy-to-use platform. In this session, you will learn how EL+T can simplify bringing in data from Salesforce, Marketo, JIRA, and other business systems to create a single view of the customer in Couchbase Cloud™.