Big data analytics framework with diagnostic

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Presenting this set of slides with name - Big Data Analytics Framework With Diagnostic. This is a seven stages process. The stages in this process are Analytics Architecture, Analytics Framework, Data Analysis.

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This image presents a structured approach to big data analytics, differentiated into four distinct categories “ Descriptive, Diagnostic, Predictive, and Prescriptive. Each card reveals a different phase in the data analysis process.
1. Descriptive analysis refers to summarizing historical data to identify what has happened until the current point. This method primarily uses data aggregation and data mining techniques.
2. Diagnostic analysis digs into that historical data to understand why something happened. It involves more in-depth data discovery, drill-down, data mining, and correlations.
3. Predictive analysis employs statistical models and forecast techniques to understand the future and answer: what could happen? It's a proactive approach that considers historical data to predict future outcomes.
4. Prescriptive analysis goes a step further to suggest actions you can take to affect desired outcomes. It combines insights from all previous stages to determine which course of action will yield the best possible result.

Use Cases:

These slides can provide valuable insights and can be leveraged across a variety of industries:

1. Finance:

Use: Improve investment strategies, manage risks, and detect fraud.

Presenter: Financial Analyst

Audience: Investment Managers, Risk Management Officers

2. Healthcare:

Use: Predict patient outcomes, personalize treatment plans, and manage healthcare resources effectively.

Presenter: Healthcare Data Scientist

Audience: Healthcare Administrators, Medical Professionals

3. Retail:

Use: Analyze consumer behavior, optimize inventory levels, and enhance customer experience.

Presenter: Market Research Analyst

Audience: Retail Managers, Marketing Teams

4. Manufacturing:

Use: Anticipate machine failures, streamline production processes, and manage supply chains.

Presenter: Operations Analyst

Audience: Plant Managers, Supply Chain Professionals

5. Telecommunications:

Use: Predict network performance, improve customer service, and tailor marketing campaigns.

Presenter: Data Analyst

Audience: Network Operations Personnel, Marketing Executives

6. Energy:

Use: Forecast energy consumption, optimize distribution, and develop renewable energy strategies.

Presenter: Energy Analyst

Audience: Utility Managers, Policy Makers

7. Transportation:

Use: Improve routing, predict transit demands, and enhance fleet management.

Presenter: Transportation Planner

Audience: Transit Authority Members, Fleet Managers

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