Data Analytics
Data analytics involves collecting, processing, and analyzing data to uncover insights, trends, and patterns that support decision-making. It is widely used in industries such as finance, healthcare, marketing, and technology.
Types of Data Analytics
- Descriptive Analytics – Summarizes historical data to understand what happened.
- Diagnostic Analytics – Investigates why something happened by identifying patterns and relationships.
- Predictive Analytics – Uses statistical models and machine learning to forecast future trends.
- Prescriptive Analytics – Recommends actions based on data insights to optimize outcomes.
Key Tools & Technologies
- Programming Languages: Python, R, SQL
- Data Visualization: Tableau, Power BI, Matplotlib, Seaborn
- Big Data Technologies: Hadoop, Spark
- Machine Learning: Scikit-learn, TensorFlow
Applications of Data Analytics
- Business Intelligence: Enhancing decision-making with dashboards and reports.
- Marketing Analytics: Understanding customer behavior and optimizing campaigns.
- Financial Analytics: Detecting fraud, risk assessment, and investment strategies.
- Healthcare Analytics: Predicting disease outbreaks and improving patient care.