Data Analytics focuses on examining, cleaning, transforming, and interpreting raw data to uncover valuable insights that drive business decisions. It utilizes statistical tools, data visualization techniques, and predictive modeling to identify patterns and trends. Unlike Machine Learning, which builds self-improving algorithms, Data Analytics primarily helps organizations optimize processes, enhance customer experiences, and make data-driven strategies.
Industries like healthcare, finance, marketing, and e-commerce rely heavily on Data Analytics to improve efficiency, reduce costs, and forecast future trends. From fraud detection in banking to personalized recommendations in online shopping, Data Analytics plays a pivotal role in transforming businesses. However, as data-driven decision-making becomes more powerful, ethical considerations such as data privacy, bias, and security are essential. Responsible use of analytics ensures fair and transparent insights, benefiting both businesses and society.
No, we’ll start from basics.
You’ll get access to the particular recorded session, or if you’ve missed lot of sessions, then we can shift you to another batch.
We’ll use Zoom App for the same.
Yes, but we’ll highly suggest to use laptop/PC.
Data Analytics is the process of examining, cleaning, transforming, and interpreting raw data to extract meaningful insights, patterns, and trends. It helps businesses and organizations make data-driven decisions, optimize operations, and predict future outcomes.
Data Analytics plays a crucial role in helping businesses make informed, data-driven decisions. Instead of relying on guesswork, companies use analytics to understand customer behavior, optimize operations, and improve overall efficiency. By identifying trends and patterns in data, businesses can predict future outcomes, stay ahead of competitors, and personalize their products or services to meet customer needs.
Data Analytics also leads to significant cost savings and operational efficiency by detecting inefficiencies and helping organizations streamline their processes. Industries such as finance, healthcare, marketing, and e-commerce rely heavily on data analytics for fraud detection, patient care optimization, targeted advertising, and trend analysis. With data becoming a critical asset, companies that leverage analytics gain a competitive edge by making faster and smarter decisions.
✅ SQL Basics, Commands & Joins
✅ Data Types, Operators & Constraints
✅ Analytical Functions & Subqueries
✅ Indexing, Stored Procedures & Views
✅ Data Cleaning & Handling
✅ Advanced Formulas & Functions
✅ Pivot Tables & Dashboards
✅ Power Query & Power Pivot
✅ Data Types, Operators & Functions
✅ Pandas, NumPy, Matplotlib & Seaborn
✅ Data Wrangling & Exploratory Data Analysis
✅ Automating Tasks with Python
✅ Building Interactive Dashboards
✅ Charts, Filters & Advanced Visuals
✅ LOD Expressions & Data Blending
✅ Publishing & Sharing Reports
✅ Data Modeling & DAX Expressions
✅ Creating & Customizing Reports
✅ Publishing & Sharing Dashboards
✅ Descriptive & Inferential Statistics
✅ Probability, Hypothesis Testing & Regression Analysis
