How can you learn data analysis software more effectively?

You should also examine your long term strategy while choosing the right software. For example, if your aim is to continuously report project progress or track a goal for leadership reporting, Tableau may be one of your top choices considering it’s advanced dashboard capabilities and UI.

Data Analysis software are plenty in the market. We often get attracted by the name, type, and brand as well. Before diving deep into the software, look at the options we already have. Excel, and Google Workspace (Kanban Board) are some of the free features which provide great visualizations beyond simple charts. I believe Excel is the core of everything. If you know how to create a dashboard on Excel, then you can ace any software easily. Then, as your data size increases, work with advanced software.

Select a data analysis software that aligns with your goals and current industry standards. For general data analysis , you can start with excel. If you want to go in visual analytics and want to make detailed dashboards, you can try PowerBI or Tableau. Some sectors may have specific software preferences due to compatibility or collaboration reasons. For example, Python is widely used in data science, but some companies prefer using R.

There are many great YouTubers who have built whole courses. Avoid watching the odd video at random. Find a strong creator and work methodically through their playlists to avoid missing patches in your knowledge.

Social Media right now has an ample number of learning resources, and tricks all for free. Even Instagram now has dedicated creators for data visualization and analysis. It is really important for one to accurately pinpoint their query and the type of things they want to use data analysis software for.

Mostly all the software providers have heaps of learning material on their websites. Make sure to leverage these on your journey to learn a particular software. You can also choose to pursue certifications on these softwares as this will provide you a motivation to keep learning more and increase your knowledge.

There are many Youtube playlists you can follow. You can even look at some shorts to check out the quality of content. For more structured curriculum, one can check out any popular edtech platform as they provide exercises along the course for better learning experience.

Use Kaggle like platforms to practise on datasets of various types and sizes, requiring a wide range of tools and theories, such an experience will (almost) directly translate as an applied skill!

What helped me the most when it came to tools like SQL was practicing with real datasets. Being able to create complex queries helped me tremendously when I made my data portfolio.

There are many platforms providing datasets like kaggle, datacamp , codebasics. You can learn to get real time data from API of different websites like stock exchanges, sports websites. It helps as data will get refreshed and modified and you'll learn to handle complexities of changing data.

Joining the community has been the most valuable step in my journey as you will get access to so many resources and perspectives from other people who are either learning or are already working in the field.

Learn, unlearn and relearn Embrace new learnings presented to you. Unlearn some of the habits or lessons from foundational courses, and relearn (this time around add some understanding and applicability of concepts). Enjoy it, you will love every bit of it!