Neetu Singla

Data visualization storytelling is an act of painting a picture by the means of charts and graphs using raw data. Telling stories through data is data that is for example sales figures or survey results taken and presented as such that can be used to tell the story. It uses graphics to create a visually attractive and understanding the complicated information. The procedure involves telling the data as a story or a narrative. Example- you might look at a company's growth over a period of time. To represent the annual revenue by a line chart, revenues can be developed over time and portrayed on an upward curve which directly implies the growth trajectory. The integration of tangible moments or milestones accents the growth of the company.

Fееdback is an invaluablе tool in thе procеss of crеating data visualizations. It sеrvеs as a guiding forcе that hеlps you rеfinе your objеctivеs and tailor your visualizations to mееt thе nееds of your audiеncе еffеctivеly. Utilizing feedback effectively for data visualization involves incorporating insights gained from various sources to enhance the quality, clarity, and impact of your visualizations. Here are several ways to achieve this: 1. Use feedback to clarify the goals and objectives of your data visualization. 2.Regularly communicate with your target audience and stakeholders to gather input. 3. Adopt an iterative approach to design. Share prototypes or early versions of visualizations.

Heatmap is a great visual that helps you see the invisible. By representing data using color and intensity, they make it easy to spot trends and patterns that you wouldn't be able to see otherwise. I have used heatmaps in my various marketing dashboards to show user engagement like Identifying areas of high and low engagement, Tracking user behavior, etc. shows where users are clicking the most on a website. The red areas are the hottest, meaning that users are clicking there most often. The blue areas are the coolest, meaning that users are clicking there less often. By understanding these user activities, you can make sure that your important calls to action are in hot spots. You can also use this information to improve your website.

Identifying data duplication could significantly impact the data trends and hence the business decisions. While working for one of our clients "TransVirtual" project, our team was tasked with visualizing monthly sales trends to identify opportunities for revenue growth. However, we discovered a data duplication issue that was impacting the accuracy of our insights. The problem was duplicate entries generated when customers used various payment methods. To address this, we implemented a deduplication strategy that involved revising the data integration process. Upon deduplication, the revised sales visualizations provided a more accurate reflection of monthly revenue trends which was very important for their stakeholders

In data visualization, it's super important to share and teach folks about the visualization so everyone can understand. And if you tell stories about the visualization in simple ways, it helps everyone get what the visualization means. I once had a client meeting where business users asked questions and it helped me change the visualization to make them better. It showed me that talking and working together makes the visualization much clearer and more interesting for the end user to use.

Whenever starting a new project, it's always better to ask the client about the brand guidelines ( a book that contains color themes, logo, etc). This is very useful while creating the wireframe for the dashboard. These guidelines serve as a design baseline, providing essential information such as approved color schemes, logos, fonts, and other visual elements that embody the brand's identity. Understanding and adhering to the brand guidelines ensures that the dashboard not only conveys the intended data insights but also aligns seamlessly with the overall brand image.