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Digital Marketing - Study Notes:

What is data visualization?

Data visualization is when you help people understand the significance of data by placing it in a visual context like a chart, a table, or a graphic. Essentially it helps to make Big Data understandable using patterns, trends, and correlations that might be undetected in text-based data.

A word cloud is a good example of data visualization. You can also use infographics to help you interpret and identify, in a visual way, key trends that you’re seeing within your existing dataset. This also enables you to highlight the key insights in a visually appealing way.

Why is data visualization important?

It enables you to make big data understandable as patterns, trends, and correlations that might go undetected in text-based data can be exposed and recognized.

Common tools

Here are some of the more common tools used to visualize data:

  • Tableau: This enables you to connect multiple data sources, and visualize data in powerful and exciting ways.
  • Microsoft Excel: You can use spreadsheet data as the source for charts and tables.
  • Microsoft Power BI: You can create dashboards, and interactive data visualizations with self-serve business capabilities.
  • Google Data Studio: With this free tool, you can connect to a variety of data sources to visualize data on custom dashboards.
  • SAS Visual Analytics: This enables you to work with self-serve analytics, visualizations, dashboards, and reports.

Advantages

Here are some advantages of data visualization:

  • You can visualize relationships between operational and business activities.
  • You can identify and act on emerging trends.
  • It’s easy to share insights.
  • It’s an effective way of communicating important information with non-analysts

Firstly, visualization enables you to visualize relationships between operational and business activities. It is very effective in ‘joining the dots’. It also really helps the organization to move forward and understand what you’re trying to achieve. Simplicity is key within these data environments, and data visualization helps you to present insights in a simple manner. This, in turn, enables people to identify and act on emerging trends faster.

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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.

ABOUT THIS DIGITAL MARKETING MODULE

Analytics
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