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Internet of Things

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Digital Marketing - Study Notes:

The Internet of Things (IOT) is a network of physical objects and devices that collect and exchange data across the Internet. It is generally used to optimize the performance of the objects themselves or to provide fresh data for analysts to use. Essentially, the Internet of Things is a means to collect and process data from daily life across a variety of products from thermostats to telematics devices which report on patterns among users.

The IOT is useful for analysts as data collection is automated and specific to the collection device. This enables analysts to unearth precise insights about device use, user behavior, or other data points.

It’s an ecosystem of interrelated computing devices all working on single or multiple tasks and collecting data. It provides you with unique identifiers and the ability to transfer data over a network. Crucially, it does this without requiring human-to-human or human-to-computer interaction.

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Jack Preston

Jack Preston is a Data Scientist working within marketing analytics, with a particular focus on strategic customer loyalty. Jack has experience working in both small-scale startups and large corporates, including dunnhumby and Notonthehighstreet. He also holds an MSc in Business Analytics from UCL where he graduated with distinction.


Jack Preston
Skills Expert

This short course covers the principles of analytics and demonstrates techniques and useful tools that you can use to develop and refine your knowledge of data analytics.

You will learn:

  • The fundamentals of data, collecting data, and processing data, including best practices, techniques, and challenges
  • The principles of web analytics, the benefits and limitations of Google Analytics, terminology for reporting, and the legalities around consent and data privacy
  • The concepts of Big Data, the processes around data, including mining, scraping, cleansing, and de-duping, and the various languages and programs for testing your data
  • The importance of AI, Machine Learning, analysis types, the value of testing hypotheses, and forecasting based on the data available
  • How best to report and present data findings to management and the different tools available to you

Approximate learning time: 3 hours