Beneficial Points of Data Analytics | India-Classifieds.com

Beneficial Points of Data Analytics, #9423

Data analytics examines data sets to draw conclusions about the information they contain. This process is typically performed with specialized software and tools.

India Country
Maharashtra State
Pune City

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Address Shivajinagar, Pune

Listing Purpose: Business Offer

Country: India

State: Maharashtra

City: Pune

Postal code: 411105

State: Maharashtra

Views Counter: 102

Owner

Divi Prajapati 09xxxxxx unhide prxxxxxx unhide

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Description

Data analytics examines data sets to conclude the information they contain. This process is typically performed with specialized software and tools. Data analytics is crucial for businesses and organizations because it provides insights to drive better decision-making, improve efficiency, and gain a competitive edge. Here’s a comprehensive overview of data analytics:

Types of Data Analytics

Descriptive Analytics
- Purpose: To understand what has happened in the past.
- Techniques: Data aggregation and data mining.
- Tools: Reporting tools, dashboards, and visualization tools (e.g., Tableau, Power BI).
- Example: Summarizing sales data to identify trends and patterns.
Diagnostic Analytics
- Purpose: To understand why something happened.
- Techniques: Drill-down, data discovery, and correlations.
- Tools: Statistical analysis software (e.g., SAS, SPSS).
- Example: Analyzing customer feedback to determine the cause of a drop in sales.
Predictive Analytics
- Purpose: To predict what is likely to happen in the future.
- Techniques: Machine learning, forecasting, and statistical modeling.
- Tools: Python, R, machine learning frameworks (e.g., Scikit-learn, TensorFlow).
- Example: Predicting customer churn based on historical data.
Prescriptive Analytics
- Purpose: To recommend actions to achieve desired outcomes.
- Techniques: Optimization, simulation, and decision analysis.
- Tools: Advanced analytics software (e.g., IBM Decision Optimization, Gurobi).
- Example: Recommending the best marketing strategy to increase customer engagement.

Data Analytics Process

Data Collection
- Gathering data from various sources such as databases, APIs, logs, and sensors.
Data Cleaning
- Removing or correcting inaccuracies and inconsistencies in the data.
Data Transformation
- Converting data into a suitable format or structure for analysis.
Data Analysis
- Applying statistical and computational techniques to extract insights.
Data Visualization
- Representing data and analysis results through charts, graphs, and dashboards.
Interpretation and Reporting
- Concluding the analysis and presenting findings clearly and effectively.