Here are just a couple tools I've worked with or heard of in the BI space
Reporting/Data Viz:
QlikView/QlikSense (What I like about Qlik is that you can build the data model in qlik, rather than having to build it in the db), Tablaeu, PowerBI, Thoughtspot, Looker, Business Objects (Built on SAP, but from what I've heard from an SAP BI user, its pure trash, lol)
Data Pipeline - ETL/ELT:
Informatica, Attunity (partnered with Qlik recently), Talend, Alteryx, Wherescape
Data Pipeline - Streaming: (still getting ramped up on this space)
Streamsets, Kafka Connect (Directly interacts with Kafka Queing system)
DataWarehousing:
TimeXtender (This is kind of a combined ETL/Data Warehouse), Snowflake, AWS Redshift, Azure SQL Data Warehouse, (Or just any Relational DB, but structured in a denormalized fashion)
Task Scheduler:
Airflow, Luigi
Languages for Data Scientists:
Python and R
And if you want to mess around with these things without the overhead of always doing admin/devops/dataops work, You can either get familiar with Docker, which will allow you to spin up microservices that run in Hyper-V environments, or you can spin up server instances in AWS or Azure.
Edit: And here's a couple of books
The data warehouse developer toolkit - Pretty much just the methodology of building out a data warehouse. I think this one is Star-schema centric
Agile data warehouse design - It brings the agile sdlc methods and applies them to buidling out a data warehouse. I like it because instead of spec'ing out a warehouse completely based on the data, its more iterative and collaborative between all levels between the business and the operational DBAs