What are the most effective ways to develop your data analysis skills?

? Fundamentals are crucial in any context, especially when dealing with data. ?? Begin by gaining a clear understanding of what data entails and its intended use. ?? Familiarize yourself with the data source as it plays a pivotal role in connecting with various tools. ? As you engage with data on different tools, you'll discern its quality, identifying errors, empty values and outliers. ??? Addressing these issues becomes vital for enhancing data quality through ETL processes. ? Subsequently, extract only the necessary data for the report view. ?? Initiate the construction of visualizations that convey compelling stories, enabling the sharing of actionable insights with stakeholders. ??

?? Consistent practice leads to mastery and I assure you, this holds true. ?? Yes , studying theoretical is vital when you want to get basics and definition in data world ? Once acquainted with the basics, refine your skills through practical application. ?? Wondering what to practice and where to start? It's simple – engage with real-world data, whether in finance, customer metrics or other KPIs. ?? Reflect on your experience, connect the data to tools like Power BI and undertake at least 10 projects to grasp real-world applications. ?? ?? Document the challenges faced and lessons learned, fostering ongoing exploration and continuous improvement in your skills. ?? ???? Keep exploring and practicing!

?? For optimal insights, a crucial step is acquiring accurate data through the ETL process. ?? ?? Once data is available, choosing the right tools becomes pivotal to maximize its potential. ??? ?? Spreadsheets or Google Sheets suffice for basic analysis, while R excels in graphical analysis, offering deeper insights. ?? ?? Power BI and Tableau stand out as premier visualization tools, crafting compelling visuals that narrate the story. ?? ??Your choice of tools should align with specific needs, preferences, expertise, budget and project goals for effective data analysis. ??

? Continuous learning is crucial, especially in the dynamic field of data analysis. ?? Explore and stay updated with the latest developments in the field. ? Practicing what you learn is essential. Platforms like Coursera or Udemy provide opportunities to stay updated and learn new courses. ???? ? Expand your insights by reading books and blogs on data analysis. Genuine connections on LinkedIn and participating in live events or webinars can also enhance your learning experience. ???? ? Connecting with experts and mentors can provide valuable guidance and support in your journey. Keep learning and Elevate your knowledge to discover new approaches and tools, this will add more value to your stakeholders and business ????

Nothing teaches you more than real life Problem Scenarios, when it comes to Data Analysis. Recently, we were checking our Fortnightly Flyer performance in Our Supermarket Retail Business. We were all tracking Value growth of the Flyer articles over base week, and were very happy to see 300 % to 500 % growth in many articles. Then someone pointed out that we were missing looking at Quantity Growth. And, when we saw the quantity growth, there was a vast difference compared to value growth, as current currency devaluation over base month was showing inflated growth. The actual quantity growth was to the tune of 80% to 200 % in same set of articles. We had a Paradigm shift and we corrected our data set accordingly.