Data Analytics
Data Analytics is the process of examining datasets to draw conclusions about the information they contain. Unlike data science (which focuses on prediction), analytics focuses on describing what happ…
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Definition
Data Analytics is the process of examining datasets to draw conclusions about the information they contain. Unlike data science (which focuses on prediction), analytics focuses on describing what happened, why it happened, and what's likely to happen next. Businesses use analytics dashboards and reports to track KPIs, identify trends, and make informed decisions.
Key Points
- Four types: descriptive, diagnostic, predictive, and prescriptive analytics
- Tools: SQL, Excel, Python, Power BI, Tableau, Google Analytics
- Business applications: sales analytics, customer analytics, operational analytics
- More accessible than data science — many roles require SQL + visualisation tools
Frequently Asked Questions
Data analytics focuses on understanding historical and current data using SQL, dashboards, and statistical analysis. Data science goes further with predictive modelling and machine learning. Analytics answers "what happened?" while data science answers "what will happen?" Many careers start in analytics and evolve into data science.
Start with SQL (essential for querying databases), then learn Excel/Google Sheets for quick analysis. Next, learn a visualisation tool like Power BI or Tableau. Python with Pandas adds powerful data manipulation capabilities. For most analytics roles in India, SQL + one visualisation tool is sufficient to start.
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