Introduction
Successful companies make informed decisions to find new opportunities, identify weaknesses, increase efficiency, and improve customer satisfaction. Data analytics is the process of examining raw data to uncover trends, and discover information used to ask and answer questions related to organizational performance.
For example, resorts and casinos might combine data from previous customer visits to determine the best time to run specific activities and games. A data analyst might take data such as customer spend and look for correlations with other factors such as the weather, regional events, or even the presence (or absence) of incentives such as food and drink.
Another example is the healthcare industry. There's an abundance of data in the healthcare industry, including patient records and insurance information. Because there's so much data, it can be difficult to manage. Data analytics allows for a thorough look at the data and can lead to a faster diagnosis or treatment plan.
In this module, you'll explore the key elements involved in data analysis. You'll look at collecting data, processing data to generate information, and visualizing results to spot trends.
Learning objectives
In this module you will:
- Learn about data ingestion and processing
- Explore data visualization
- Explore data analytics