The Internet of Things increases the opportunity for people to create and invent new devices due to lower costs and greater access. The resulting explosion of new types of devices and solutions further contributes to the exponential growth of data in the IoT. Organizations are now critically dependent on the collection, storage and analysis of this data to extract information and gain insights for the business. Making good decisions depends on good data. As the amount of data grows, decision makers increasingly rely on data analytics to extract the required information at the right time and in the right place to make the best decision.

Students who complete the Big Data & Analytics course will be able to perform the following functions:

●  Explain how businesses can extract information and insights from IoT Data.

●  Understand the steps of the Data Analysis Lifecycle and perform these tasks.

●  Understand privacy and security aspects of data.

●  Explain the different types of data analytics: descriptive, predictive and prescriptive.

●  Use Python to create a data pipeline to acquire, manipulate and visualize sensor data.

●  Apply exploratory data analysis to extract insights from data.

●  Understand how Machine Learning algorithms can be used for predictive analytics.

●  Present and communicate using data storytelling.

●  Describe the evolution of data management technologies from SQL to NoSQL.

●  Understand and explain the evolution of a modern data center computing platform and be aware of distributed scalable Big Data solutions such as Apache Hadoop, Cassandra and Spark.