It turns raw numbers and scattered information into meaningful insights. Companies use these insights to improve sales, cut costs, personalize customer experiences, and make smarter, risk-aware decisions.
Yes — Analytics focuses on understanding what happened and why, using dashboards, statistics, and trend analysis. Data Science goes deeper — creating predictive models and algorithms that forecast what is likely to happen next.
100%. Many professionals transition from business, marketing, operations, finance, and HR. Curiosity, logical thinking, and willingness to experiment with data matter more than having a purely technical background.
The most widely used tools include:
Excel (advanced)
SQL
Tableau / Power BI
Python for data manipulation
These tools help you clean, visualize, interpret, and communicate data results effectively.