NoSQL technology is al most mainstream now. And with self-managed agile development teams embracin g the flexibility of JSON in NoSQL document databases, the field of data mo deling is too often strictly associated with relational databases, and henc e viewed as too rigid and cumbersome. The data modeling actors, roles, life cycle, processes, and tools are rapidly changing in that context, and the e ntire field is re-inventing itself to remain relevant and demonstrate its c ontribution. As it turns out, data modeling becomes even more important whe n the guardrails provided by normalization have been taken down. At the sam e time, unstructured and polymorphic big data is creating challenges both i n terms of data governance (in the context of privacy regulation -- GDPR an d PII) and the ability of enterprises to leverage the mountains of informat ion accumulated. Data modeling is now used in production on a daily basis t o help discover how data has been stored, in order to help query it effecti vely and keep it compliant. In this session, you will learn a completely ne w approach to data modeling, to leverage the power and flexibility of:
\ n\n MongoDB\n AWS DynamoDB\n Couchbase\n Azure Cosmos DB\n Elasticsearch\n Cassandra\n HBase\n Google Firebase/Firestore\n MarkLogic\n Other NoSQL and multi-model databases\n\n
\nYou will also learn how
data modeling helps enterprises migrate from RDBMS to NoSQL.