Reports of the death of data modeling are very much premature. NoSQL does not eliminate the need for data models. Big data, in fact, makes modeling more important. It is imperative with growing volumes and kinds of data that we know what is in our databases. If you still use RDBMS then you continue to need relational models. If you have star schema and OLAP then you need dimensional models. If you’re building a data lake, using document stores, or using graph databases then you need to adopt the new practices for data modeling in the age of big data. When schema is defined to store data (schema on write) data modeling is an essential design activity. When schema is defined as data is explored and analyzed (schema on read) data models are the means to capture data knowledge. No, data modeling is not dead. But in some organizations it is rapidly becoming a lost art. Don’t let it happen to you. TDWI’s (whatever you choose to call the track) will build skills with established data modeling methods and get you started with new techniques that have emerged to model the complex structures found in big data and NoSQL databases.