The Story of Data - Part 5

We at Powered By Data are passionate about supporting talent when we see it. This final part of this phase of our "Story of Data" was written by Oliver Thomas who is not only an excellent copy writer, but an astute entrepreneur who has a fantastic future ahead of him.

This is the fifth and final post in a multi-part series that delves into our approach to partnering with organisations to drive impactful outcomes. In this post, we will focus on the Data Visualisation and Exploration phase – this phase marks the conclusion of the Realm of Enablement and readies us for the next steps in the Realm of Positive Business Change. All of this can be found on our website at www.wearepoweredbydata.com/datastory where we will build up to the full story as we go.

Data Visualisation and Exploration

The Data Visualisation and Exploration phase begins after the data has been cleaned and prepared. This is where we begin to make sense of the data and extract some preliminary insights.

It is important to note that visualisation and exploration are closely related, but distinct. Data visualisation is the process of creating graphical representations of data to make it more easily understandable and interpretable. By creating charts, graphs, maps, and other interactive forms of information delivery, we can assist our clients in identifying patterns, trends, and insights that would otherwise be difficult to discern from raw data. We utilise a variety of tools and techniques to create these visualisations, ensuring that they are easy to understand and interpret.

In contrast, data exploration is the act of actively engaging with the data to uncover new knowledge and trends. It involves a cyclical process of experimenting with various visualisations and examining different subsets of data. Techniques such as clustering, aggregation, and filtering are utilised to delve deeper into the data and uncover information that will aid in our subsequent analysis later down the line.

We use best practises for data visualisation and information delivery to help our clients get the most out of this stage. With our help in visualising and exploring data, organisations can identify patterns and trends that would otherwise be unnoticeable. That being said, the information obtained in this phase is primarily to fuel deeper analysis further down the line rather than to drive immediate business change – it is important to be aware of the significant hazards that come with using basic visualisations to inform substantial decisions.

Listed below are a variety of types of visualisations that allow clients to very quickly understand their data, and some of their appropriate use cases:

Line Charts

We utilise line charts to help our clients understand the trends and patterns in their time-series business data over time. Line charts are commonly used to display data such as sales, revenue, and customer engagement, making it easy for our clients to identify any fluctuations or trends in their data.

Bar Charts

Bar charts are an essential tool for our clients to compare values across different categories of business data. We use bar charts to display data such as market share, employee performance, and customer demographics, making it easy for our clients to conduct side-by-side comparisons of their categorical business data.

Heatmaps

Heatmaps are a powerful tool that we use to visualise our clients' business data in two dimensions and identify patterns and trends in their spatial data. We use heatmaps to display data such as customer location, store performance, and supply chain logistics, assisting our clients to uncover and discern patterns and correlations in their data through multiple variable analysis.

Scatter Plots

Scatter plots are also an excellent tool that we use to help our clients understand the relationships between different variables in their business data. We use scatter plots to display data such as customer demographics and purchase history, making it easy for our clients to identify patterns and trends in their data with multiple variables.

Pie Charts

We often utilise pie charts as a method for helping our clients comprehend the proportionality of various categorisations in their business data. We use these charts to showcase information such as sales of products, customer segmentation, and marketing campaign results, providing a simple way to view data from a relative perspective and directly compare different sections of data. Pie charts however are frequently misused, being less effective for comparing multiple values, but working well for illustrating one or two values in relation to the whole.

Some examples of basic exploration methods include, but are not restricted to:

Clustering

The process of grouping similar data points together based on their characteristics. This allows for the identification of patterns within the data, and can be used to group similar customers, products, or any other data points together. For example, clustering can be used to segment a customer base by demographics, purchase history, or any other relevant characteristics.

Aggregation

The process of combining data points to provide a higher-level summary of the data. This is typically done by taking the average, sum, or other aggregate function of a set of data points. For example, aggregation can be used to find the total sales of a particular product or the average customer satisfaction score across a certain time period, and for a range or dimensions.

Filtering

The process of selecting a subset of data based on certain criteria. This can be used to focus on specific aspects of the data that are of interest, such as a particular product or a specific time period.

Data visualisation and exploration are not just about creating appealing images. They are about turning data into insights that can help organisations achieve their goals. We work closely with our clients to understand their objectives and use visualisation and exploration techniques to help them reach them.

If you're interested in learning more about how we can help you turn your data into actionable insights, visit our website at www.wearepoweredbydata.com or reach out to Anna Blackwell at anna.blackwell@wearepoweredbydata.com. Keep informed about new posts in this series by following us on LinkedIn. We are dedicated to helping organisations unlock the full potential of their data and drive success.