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Business Analytics Using Forecasting

Discover how business can harness the power of big data to make better predictive analysis.

Business Analytics Using Forecasting
  • Duration6 weeks
  • Weekly study3 hours

Learn how to use data to create powerful business forecasts

Organisations currently collect a vast quantity of data about suppliers, clients, employees, citizens, transactions, and much more. However, many are unaware of the predictive power this ‘big data’ has if anaylsed correctly.

On this course, you’ll learn about forecasting using big data, exploring how it’s used by business as an important component of decision making.

You’ll examine how to define a forecasting task and workflow. You’ll understand how to evaluate forecasting performance, analysing different forecasting methods. Ultimately, you’ll be able to implement your own practical forecasting process.

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Skip to 0 minutes and 10 secondsHello I'm Galit Shmueli, a professor at National Tsing Hua University's Institute of Service Science I design and teach courses on Business Analytics to help students understand not just how to crunch data but why to crunch data. People, societies, products and processes generate lots of data. Data science and business analytics have evolved as more and more data becomes available at higher resolution and at higher frequency. Quantitative forecasting is the science of using time series data for generating forecasts. In other words, extrapolating a series of measurements into the future. Forecasting plays an essential role in decision making in almost any environment you can imagine where data are collected over time. Here are just a few examples.

Skip to 1 minute and 2 secondsForecasting the number of hourly or daily customers at a restaurant, bank, or other service provider can help with staffing decisions, inventory management, cash flow planning, service decisions, and even space design and choice of technologies to use. Forecasting is essential also in transportation. Think about bicycle sharing systems. Forecasting the demand for bicycles at each station at different times during the day can help with smarter distribution of bikes expansion of bike stations and planning new locations and bike routes. It can even help with maintenance scheduling. With today's Internet of Things (IoT) automated sensor data can help forecast usage of offices, restrooms, vending machines, and other facilities. Such forecasts can help with staffing, replenishment, and other service operations.

Skip to 1 minute and 59 secondsIt can also support environmentally minded decision making and design. In this course, we’ll focus on how to create a forecasting solution. You'll learn about different popular forecasting methods and algorithms but we're also going to focus on the entire forecasting process. This means we're gonna look at how to define a forecasting problem, how toevaluate the performance of a forecasting method, and, importantly, how to tie the forecasting analytics with the business problem. This course is for you if you'd like to extend your predictive analytics capabilities to the forecasting domain and time-series domain or if you have to generate forecast for your job. Maybe you'd like to become more knowledgeable consumer of forecasts.

Skip to 2 minutes and 50 secondsOr maybe you're just curious to learn scientific and practical approach to forecasting time series. The learning in this course is based on weekly activities In each week, you'll be expected to read a chapter in the textbook, to watch a few short videos, and to work on an activity or analysis related to forecasting. Finally you'll engage in an online forum. This combination is designed to help you learn about forecasting in an active and engaging way. I hope you now have a better idea about what this course is about and what you might learn from it. Welcome to the community of learners on time series forecasting or as we say here 歡迎光臨(Huānyíng guānglín)!

What topics will you cover?

  • Goal definitions
  • Data visualisation
  • Data modeling
  • Performance evaluation
  • Model deployment

What will you achieve?

By the end of the course, you‘ll be able to...

  • Describe business challenges and opportunities that call for forecasting
  • Evaluate performance of a forecasting solution
  • Apply and be familiar with popular forecasting methods
  • Explore, identify and model different types of patterns in time series
  • Develop a forecasting solution using forecasting methods

Who is the course for?

This course is for anyone who wants to understand how big data can help their business or organisation’s decision-making process. You will need to be familiar with basic statistical methods, including linear regression, as well as have basic knowledge of Excel and R software.

What do people say about this course?

A great introduction to forecasting. It cleared up some problems that I was finding where I was trying to overfit to Holt-Winters and not getting good results. The training and validation periods were a bit of an eye-opener. I got a bit lost on autoregression techniques particularly ARMA and ARIMA, but I will go through those modules again, to try and make sense of it. I also purchased the book so this should also help. The R programming language is much more powerful than I had thought and the step by step process will help. There are some good tutorials on how to use it on the web that has been helpful. Thank you for putting this course online.

Jonty Pearce

Who will you learn with?

Distinguished Professor @ NTHU, Taiwan. Pioneered business analytics courses at U of Maryland, Indian School of Business, NTHU & Statistics.com. Read about her research & textbooks at galitshmueli.com

PhD Candidate at NTHU, Taiwan. Research interests are methodological advancements and predictive implementations of PLS Path Modeling.

Ph.D. student - Institute of Service Science, National Tsing Hua University
Lecturer - University of Economics and Law, VNU - HCM
Specializing in Business Analytics, Data Mining, and Service Science

PhD Student at National Tsing Hua University, with a focus on data science ethics.

Who developed the course?

National Tsing Hua University

National Tsing Hua University in Taiwan consistently ranks as one of the premier universities in East Asia.

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