If you have a job, use the industry you are in as a starting point to explore your aptitude and interest. You might like to write lots of SQL queries, extract insights, and make interesting presentations with spreadsheets and slides. This is as useful and important as someone writing data engineering pipelines in Python or Spark.

Or you may wish to architect end to end solutions and may want to pick up more engineering skills and write lots of Python code.  It is hard to know what you like unless you try many things. Your job may not allow you to try many things.  Instead, you can take some time out of your routine to explore other aspects of data work.

You need to improve your skills continually in one or two key areas. Someone who has expert level skills in Excel can do a lot more than someone who has introductory skills in SQL, Python, and R. It isn’t how many tools you know that will give you the most mileage, but how well you know a few essential tools.

Your skills in SQL need to keep improving. Knowledge of BI tools like Tableau/PowerBI are essential in the industry. Presenting data and insights in a spreadsheet (pivot table, charts) is a valuable skill for any Analyst.

Want to know what Analytics reports are common in other industries? Search with “Product Analytics in Healthcare Vendors” or “Product Analytics in Automotive case study” and research the top 10 results.

Researching the results requires reading the articles and writing a summary in your personal notebook. Do this for a specific vertical and you will quickly learn what is important in a particular industry.

Similarly, read the blogs of Analytics vendors (there are many). These companies often feature their customers and the kinds of projects and problems they have solved for them using their offerings (see Fivetran blog).