Next steps

To continue your exploration of TimescaleDB, here are some valuable next steps to help you on your way to becoming a time-series superhero.

One of the first things most developers want to do is look at the data they’re currently working with in the database. There are a number of methods for importing data that you currently have, whether it exists in another database or a .csv file.

Working with sample data can teach you a lot about TimescaleDB, but you might like to try ingesting market data in real time. Check out our related tutorial Ingest real-time financial websocket data and continue ingesting data directly from the financial API.

Time-series data is perfectly suited for viewing with tools like Grafana, Tableau, and Power BI, to name a few. Once you can see trends and query for specific data features using relational data, a whole new world of insights begins to open up.

While this may be the century of big data, the greatest power often happens in connected applications that help turn data into value to users. Using time-series data effectively means you need to get your code connected and working as efficiently as possible.

See the growing list of language Quick Starts to get you up and running with TimescaleDB, including best practices.

Have a look some of the other datasets provided for you to dig deeper into time-series data and data analysis using TimescaleDB.