Data Science in FMCG

Understand key transformation blueprint in CPG industry with Data Science in FMCG course.

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Intermediate

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1.5 Hrs

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4.4K+

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Data Science in FMCG

1.5 Learning Hours . Intermediate

Skills you’ll Learn

About this course

This course on how Data Science, in a few of the many ways, unwraps, market, evolution, optimizes digital manufacturing that underpins and nurtures a key transformation road map in the CPG industry. This course will give a glimpse based on real-world scenarios, with a solution and industry insights, and on what it takes to make the impact.

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Course Outline

Introduction to Transformations in FMCG through Data Science
How does a CPG organization work?
How Data Science can create a strategic impact?
Understanding and Modelling the problem
Probability Distribution - Refresh
Model, Parameters and Variables
Gibbs Sampling Algorithm
Technology framework
Introduction to Optimizing manufacturing in Digital Age
Throughput Optimization
Canonical form for Optimization Modelling

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4.61
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Ratings & Reviews of this Course

Reviewer Profile

5.0

This course has really developed me. I hope to familiarize myself with the graph flow chart of data science and analytics in a manufacturing company.
I hope for more training ahead on data analysis, business analysis, AI engineering, and lots more. And to the organizers, I really appreciate the privilege to pass through this phase of learning. Thanks so much! 💪💪

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Learn at your own pace

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Master in-demand skills & tools

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Test your skills with quizzes

Data Science in FMCG

1.5 Learning Hours . Intermediate

Frequently Asked Questions

How do you analyze FMCG sales data?

FMCG sales data can be analyzed in a number of ways, depending on the specific information that is being looked at. Some common ways to analyze FMCG sales data include looking at sales by geographic region, product category, or specific product. Additionally, to see how sales are changing over time, FMCG sales data can be analyzed in terms of trend data.

How can I get FMCG data?

There are a few ways to get FMCG data. One way is to purchase a market research report from a reputable market research company. Another way is to access public databases, such as Nielsen or Euromonitor, which contain FMCG data. Finally, you can contact FMCG companies directly and request data.

How is forecasting done in an FMCG company?

Several distinct methods can be used to forecast demand in an FMCG company. Common methods include trend analysis, regression analysis, and time series analysis. Learn Data Science in FMCG through Great Learning’s free course and understand the various analyses.

Why is demand planning important for FMCG companies?

FMCG companies need to have an accurate demand plan in order to know how much product to produce and how to allocate their resources. An accurate demand plan can help a company avoid over-or under-producing and can help them optimize their inventory levels.

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Data Science in FMCG Course

Data Science is a multidisciplinary field that involves using statistical, computational, and mathematical techniques to extract insights and knowledge from data. It encompasses various aspects of data analysis, including data collection, data cleaning, data modeling, and data visualization. The goal of data science is to use data to inform decision-making and drive positive outcomes for organizations.

In the context of the Fast Moving Consumer Goods (FMCG) industry, data science plays a critical role in helping organizations to understand consumer behavior, market trends, and sales performance. By using data to make informed business decisions, FMCG organizations can improve their marketing strategies, product offerings, and customer engagement.

For example, data science in FMCG can be used to identify the most popular products and understand consumer preferences and purchasing patterns. This information can then be used to optimize pricing strategies, improve product development, and create targeted marketing campaigns.

Additionally, data science in FMCG can help organizations to track and analyze sales data, customer behavior, and market trends. This information can be used to identify areas for improvement, such as inventory management and supply chain optimization, and to optimize overall operations for maximum efficiency and profitability.

The benefits of using data science in FMCG are numerous. By using data to make informed business decisions, FMCG organizations can improve their marketing strategies, product offerings, and customer engagement. Additionally, data science in FMCG can help organizations to identify areas for improvement and to optimize their overall operations for maximum efficiency and profitability.

In conclusion, data science plays a critical role in the FMCG industry. By collecting and analyzing data, FMCG organizations can make informed business decisions and improve their marketing strategies, product offerings, and customer engagement. Whether you are just starting out with data science in FMCG or looking to take your organization to the next level, the benefits of this technology are clear.
 

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