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5 year data science analytics roadmap

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Presenting 5 Year Data Science Analytics Roadmap PowerPoint Template. This PPT presentation is Google Slides compatible hence it is easily accessible. You can download and save this PowerPoint layout in different formats like PDF, PNG, and JPG. This PPT theme is available in both 4,3 and 16,9 aspect ratios. This PowerPoint template is customizable so you can modify the font size, font type, color, and shapes as per your requirements.

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Content of this Powerpoint Presentation

Description:

The image depicts a "5 Year Data Science Analytics Roadmap" PowerPoint slide. It outlines a strategic plan for developing skills and competencies in data science over five years. The timeline is divided into five columns, each representing one year, with milestones placed across four horizontal tracks that represent different areas of data science:

1. Fundamentals - Including "Data Scrubbing," "Exploratory Data Analysis," and "Regression."

2. Statistics - With milestones like "Reading CVS Data" and "Training & Testing Data."

3. Machine Learning - Not detailed in this snippet but would include advanced analytics techniques.

Each track has milestones marked with colored dots and lines that indicate the progression and expected time to achieve each step.

Use Cases:

This type of slide can be utilized across various industries for multiple purposes:

1. Technology:

Use: Guiding tech companies in developing data science capabilities.

Presenter: CTO or Data Science Manager.

Audience: Technical teams.

2. Education:

Use: Curriculum development for data science programs.

Presenter: Academic Curriculum Planner.

Audience: Educators and students.

3. Healthcare:

Use: Implementing data analytics for patient data management.

Presenter: Healthcare Informatics Specialist.

Audience: Medical staff and healthcare administrators.

4. Finance:

Use: Advancing analytical competencies for financial forecasting.

Presenter: Chief Financial Officer.

Audience: Analysts and finance professionals.

5. Retail:

Use: Developing predictive models for customer behavior.

Presenter: Marketing Director.

Audience: Marketing and sales teams.

6. Manufacturing:

Use: Leveraging data science for operational efficiency.

Presenter: Operations Manager.

Audience: Operations and production teams.

7. Government:

Use: Training for public sector analysts in data-driven decision-making.

Presenter: Public Administration Trainer.

Audience: Government employees and policymakers.

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