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Prescriptive Analytics for Decision-Making in BI

This comprehensive course emphasizes the incorporation of prescriptive analytics into the Business Intelligence (BI) framework.

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Certificate :

After Completion

Start Date :

10-Jan-2025

Duration :

30 Days

Course fee :

$150

COURSE DESCRIPTION:

– This comprehensive course emphasizes the incorporation of prescriptive analytics into the Business Intelligence (BI) framework, aimed at enhancing decision-making processes and improving results.
– Participants will acquire skills in utilizing data-driven methodologies and tools to propose actionable solutions and strategies for intricate business challenges.
– The curriculum integrates theoretical principles with practical projects, equipping learners to effectively apply prescriptive analytics in various contexts.
– By the end of the course, attendees will be prepared to utilize prescriptive analytics to make well-informed and strategic decisions in real-world situations.
– The program is designed to foster a deep understanding of how prescriptive analytics can be employed to optimize business outcomes and drive success.

CERTIFICATION:

  1. Upon completion, participants will earn a Certificate in Prescriptive Analytics for Business Intelligence, signifying expertise in applying prescriptive analytics to solve business challenges and drive decision-making.

LEARNING OUTCOMES:

By the conclusion of the course, participants will possess the skills to:

– Comprehend the significance of prescriptive analytics as a vital component of the business intelligence (BI) framework.
– Distinguish among the three types of analytics: descriptive, predictive, and prescriptive, highlighting their unique functions and applications.
– Employ optimization models and simulation methodologies to produce practical recommendations that can be implemented in various contexts.
– Utilize prescriptive analytics in tangible business situations across diverse sectors, demonstrating its versatility and impact.
– Seamlessly incorporate prescriptive analytics tools with BI solutions such as Power BI and Tableau to enhance data-driven decision-making processes.

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Course Curriculum

Introduction to Prescriptive Analytics
  1. Overview of analytics: Descriptive, predictive, and prescriptive
  2. The value of prescriptive analytics in decision-making
  3. Key tools and techniques in prescriptive analytics
  4. Real-world examples: Applications of prescriptive analytics
Data Preparation for Prescriptive Analytics
  1. Data cleaning and transformation for prescriptive analysis
  2. Exploring data relationships and dependencies
  3. Managing structured and unstructured data sources
  4. Hands-on: Preparing a dataset for prescriptive modeling
Optimization Techniques
  1. Linear programming and optimization models
  2. Constraint management in optimization problems
  3. Applications in logistics, resource allocation, and pricing strategies
  4. Hands-on: Solving an optimization problem using Excel Solver
Simulation for Decision-Making
  1. Introduction to Monte Carlo simulations
  2. Scenario planning and risk assessment
  3. Applications in financial modeling and supply chain management
  4. Hands-on: Developing a simulation model in Python or R
Tools and Platforms for Prescriptive Analytics
  1. Overview of popular prescriptive analytics tools (e.g., IBM Decision Optimization, SAS, Python libraries)
  2. Integrating prescriptive models with BI tools like Power BI and Tableau
  3. Automating decision-making workflows with prescriptive analytics
  4. Hands-on: Embedding a prescriptive model into a BI dashboard
Industry-Specific Applications
  1. Prescriptive analytics in finance: Portfolio optimization and risk mitigation
  2. Applications in healthcare: Resource allocation and treatment planning
  3. Use cases in retail: Pricing strategies and inventory management
  4. Real-world examples: Industry-specific case studies
Ethical Considerations and Challenges
  1. Ethical use of prescriptive analytics in decision-making
  2. Addressing biases in prescriptive models
  3. Data privacy and compliance considerations
  4. Strategies to overcome implementation challenges
Communicating Prescriptive Insights
  1. Visualizing prescriptive analytics outputs effectively
  2. Tailoring recommendations for diverse stakeholder groups
  3. Building trust in data-driven recommendations
  4. Hands-on: Presenting prescriptive insights through a dashboard

Training Features

Interactive Video Lessons

Comprehensive guidance on prescriptive analytics concepts and tools.

Practical Exercises

Hands-on tasks to apply optimization and simulation techniques.

Case Studies

Real-world examples of prescriptive analytics in action.

Expert-Led Sessions

Weekly Q&A and workshops with industry professionals.

Capstone Project

Solve a real-world business problem using prescriptive analytics.

Certification

A globally recognized certificate upon completing the course.

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