The Fundamentals: Data Storytelling and VisualizationBusiness Agents convert their big data to visualizations allowing them to demonstrate the insights with the only a couple of graphs. Conversely, the following business approach may remain uncovered if words do not convey them. Without dialect, businesses find it difficult to drive their message and influence their audience. Generally, advertisers, salespeople and business people are the storytellers. They are accountable for their data storytelling; getting the information and message across to their audience. Successful data storytelling in business must be centered on fitting the story to the audience and picking up the correct data visualization type to balance the story. Here are a few tips on how to prepare the best storytelling to go with your data. The nuts and bolts with regards to storytelling: you should pick your data visualization deliberately. Without a doubt, unique perspectives answer distinct inquiries, so be cautious while choosing how to visualize it. To help you in this activity, you will require a data visualization tool. Salesforce Einstein Analytics gives you a comprehensive view of options to look over such as line graphs, bar diagrams, maps, scatter plot, treemap, funnel, origami and many more with custom query and dashboard design functioning. This advanced BI tool helps both in investigating the data and visualizing it, empowering you to communicate the insights in a meaningful way. There are two kinds of storytelling, writer and reader-driven narrating. A writer driven storytelling is static and legitimate as it dictates the investigation procedure to the audience. Whereas, reader-driven narrating, enables the viewer to structure the investigation all alone – pick the data visualization that they think is important and connect with them by drilling down the details or selecting the metrics they need to see visualized. Accordingly, they can join for insights that are essential for them and fit well out of data. Data storytelling should always start with a problem statement. What is the principal take away from the data storytelling? Our motivation will be to inspire the audience to make a specific move. Hence, rather than thinking about the business objectives, attempt to conceive what the audience members are searching for. Every individual from the audience has come to understand the data storytelling to gain benefit for himself. The end goal; to better live up to the desires and gain trust. Put the objectives first and let them decide the line of the story. We at AppShark endeavor to learn as much as we can about our target audiences/clients. We place ourselves in their shoes for instance, who are they? What is their business? What is their business problem? What specific solution do they need? What esteem can they draw from their data with self-drill down?
Step by Step Instructions to Present a DashboardIn a second section, we will look into a specific type of data storytelling known as “dashboarding”. Business dashboards are currently driving the way with regards to envisioning business insight. Einstein Analytics enables customers to engage with real-time data and offer a more dynamic approach to deal with displaying data contrasted with a rigid, traditional way of data visualization in other BI tools. The current question is: What is incredible dashboarding? Here are our tips on the best way to transform your data into a story and control your particular organization through dashboard storytelling.
1. Set up your planTo begin with, the best way to show a dashboard is to layout your introduction. Like every great story, the plot needs to be clear, the problem should be clearly stated, and a result foreshadowed. You need to ask the right questions with regards to investigating the data to get insights, in addition to asking the right questions with regards to exhibiting such information to a specific group of audiences: What information do they need, and want to see in the dashboard? Attempt to be reason-driven to have the best dashboarding results, although you should not entrap yourself in a rigid format that is unchangeable.
2. Make your story with the combination of dataConsolidating jargons, millions of dataset, complex mathematical concepts and making a story that individuals can comprehend isn’t so simple. It’s critical to see how the distinctive components consolidate together in data narration. However, when the story is combined with data, it enlightens the audience to what’s going on with the data and why a specific insight is essential. Plentiful context and critique are required to understand the idea entirely. However, when visuals are applied to the data, it is easier to explain to the audience the insights that they wouldn’t see without diagrams or charts. Numerous instances where anomalies in the data would stay uncovered in the data tables without the assistance of data visualization. Lastly, when accounts and visuals are consolidated, they can draw in or even engage a group of people. When you join the correct visuals and narration with accurate data, you have a data storytelling dashboard that can make an impact and drive change.
Figure 1. Data Storytelling with Combination of Data
Instances of Storytelling DashboardsFinally, don’t be hesitant to try various approaches to deal with data storytelling. Make a dashboard data storytelling plan that enables you to investigate and test multiple alternatives and realize what will engage your audience members. We have already gone through the theories on how to deal with data storytelling and how to introduce a dashboard. Here is one instance of dashboard with storytelling we have built for one of our clients.
Default Loan Value Reduction DashboardThe company is a leading peer to peer lending company that directly connects the borrowers and potential lenders. The data they have includes the borrower’s behavior and characteristics. AppShark’s analytics team has implemented Einstein Analytics to create data storytelling dashboard to know and improve the loan repayment, and leading causes which affect the loan default. To understand the dataset in a better way, we have built dashboards in advanced analytics that comes under the exploration phase. The KPIs tracked here are focused on the loan metrics such as loan amount sanctioned, interest rate, average FICO score, defaulted loan amount by time, loan term and location. It lets us know what the factors affecting loan default are, current trends in lenders behavior with further drill down by loan subgrade, loan type, and location for the enhanced analysis.
Figure 2. Screenshot of Default Loan Reduction Dashboard