The Flux language offers a declarative approach to data transformation and analytics, transforming data by pipe-forwarding it between functions where each function transforms the data. The fundamental components of Flux include `from()`, `range()`, `filter()`, `yield()`, and `aggregateWindow()` functions. InfluxDB users can convert common InfluxQL queries into Flux queries to gain a deep understanding of the language, even without studying its basics or annotated CSV output format. Flux provides more power and flexibility than InfluxQL, allowing users to perform joins, manipulate timestamps, filter with conditional logic, conditionally transform data, and write custom functions for advanced analytics. The language requires a shift in thinking about data structure, hierarchy, and shape, and users can leverage the `map()` function to transform each record of the data piped into it. With Flux, users can create alerts and notifications, write median absolute deviation anomaly detection algorithms or Naive Bayes classifiers, and perform math across measurements. The language offers a far improved developer experience compared to TICK scripts, allowing for more flexibility and functionality in data analysis and processing.