Depending on your role, your work will require you to learn about new datasets, understand how data relates to the business, and communicate insights through reports, dashboards, and analysis. The tools you'll likely use are SQL, a Business Intelligence (BI) tool (e.g. Power BI, Tableau), and perhaps a scripting language like R or Python for more advanced analytics.
The most successful BI analysts have a good command of the technical tools required to manipulate, analyze, and present data as well as a curiosity about the business. You should view yourself as a partner with your business counterparts, not just someone who receives tickets to build reports or dashboards.
Your typical day might start out by reading your emails and reading your company Slack posts or messenger posts. You will likely get small requests for analytics help this way. Your manager will likely assign projects for you to work on and provide you with other contacts that will support you. So you might have a meeting or two (in-person or virtual) to get acquainted and better understand the goals of your projects.
From there, you may do some work to get access to large data sets, getting them exported into a spreadsheet for analysis using pivot tables and charts within Excel or Google Sheets spreadsheet applications. Or you may get trained on how to use Google Analytics, or my personal favorite, Tableau analytics. Tableau is owned by Salesforce and I believe it to be the best analytical tool to help you visualize trends in your data and better determine hypotheses or key insights about your company to share and educate others.
You will likely spend a great deal of your time studying data, identifying outliers, creating charts from the data, checking things for accuracy, and then exploring trends in the data set. You might also see anomalies in your data (ie a big spike during one month) and then schedule some calls to ask various experts what might have happened during that time. Much of this work will culminate in you sharing your insights and learnings with your manager and/or key decision makers that will make use of the data. They may ask you to dive deeper into the data or add additional data perspectives to learn more.