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Supercharged: Breaking Down an Interactive Dashboard

Data visualization doesn’t have to be boring. In fact, it’s better when it’s not. An interactive dashboard delivers more powerful Business Intelligence (BI) and higher organizational engagement than the traditional, read-only charts built with outdated, legacy BI tools.

In this article, we breakdown the key features of an Astrato interactive dashboard, explaining the technology behind it and how it delivers powerful insights through an intuitive, no-code platform. We spoke with the designers, Elizabeth and Piers, to understand why they chose certain technical features and design choices. 

Introducing the dashboard

The dashboard below utilizes some of Astrato’s unique and powerful interactive features – like Writeback and AI-Insights to analyze the Seattle housing market and reveal long-term trends as well as compelling details. 

The user can enter their specifications for a house – number of bedrooms, number of bathrooms, ZIP code, square footage – and the dashboard provides an estimated price. The supplemental data tab visualizes regional trends in the Seattle housing market, showing how average prices have changed since 2019, and which ZIP codes are the most affordable. Actionable insights can be generated using Astrato’s AI-Insights feature and then shared directly from the platform. 

This is just one of the incredible data apps built by the Astrato team, but you can explore more of these apps on a wide range of topics, such as how Elon’s tweets affect Tesla stock price, or an interactive sales CRM workbook, plus many more.

In this article, we’ll break down this dashboard into its component parts, analyzing the key features, the technology behind them, and how they offer an advantage over legacy BI tools. 


Data visualization feature #1: Writeback

The star of this interactive dashboard is the price estimation feature where users can input the specifications of their desired home and get an idea for how much it will cost. This is possible through Astrato’s Writeback feature, which transforms the interface from a ‘look but don’t touch’ chart, to a dynamic, interactive dashboard. In this example, Writeback directs the user’s specifications to Snowflake’s Snowpark, where a python program calculates an estimated price, which is what you ultimately see on the dashboard. 

Writeback is also used in the ‘Similar Homes’ section. The distinction is that here, SQL is used in Snowflake to create a view (similar to a table). The code sets parameters around the user’s requirements (e.g. plus or minus a bedroom) to show properties most similar to what the user is searching for. 

 

In both cases, Writeback filters and retrieves information from a database, but it can also be used to add new data entries in real-time, or comment useful context to existing data. 

For example, business users can input sales data directly into KPIs, keeping important metrics up to date with business activity. This two-way data flow, where data can be both viewed and managed through the dashboard, allows users to remain in their BI application while updating the data at its source. The value of this is two-fold: data is kept up to date, and actionable insights are produced more efficiently.

The dashboard was designed in this way to allow the user to directly interact with the data. Interaction with the data is especially valuable when the user is looking for specific information. In our example, someone looking to buy a house might be interested in broader market trends, but what they really want to know is what they can afford. Writeback answers this immediately, querying the data based on the user’s interests and providing an estimated price. 

Data visualization feature #2: AI-Insights

Better communication, better BI insights. The ‘Send insights to Slack & Email’ button uses OpenAI to generate visual and text-based BI, identifying trends, detecting anomalies, and offering recommendations. A conventional interactive excel dashboard might feature a pivot chart or filter system; AI-Insights makes data analysis even more accessible, where the work is done for you in just one click. The information can then be shared directly from the platform. No need to screenshot, attach, or embed. 

This means more efficient communication, but also better BI. The insights update when the data does, meaning business decisions are based on the most up-to-date information. Employing AI in this way also drives engagement from users with lower data literacy or those simply bored of looking at the same old dashboard. Higher adoption across an organization builds true data-driven culture, one that measures what matters and takes action accordingly. 

 

How do these features aid visualization: The interactive scatter plot

Properties similar to the user’s ideal home are displayed via an interactive scatter plot. The X-axis measures square footage and the Y-axis shows price, with each dot marking a property. It’s interesting to note that the general trend is (unsurprisingly) that price rises with square footage. 

But! When the demo user enters their specifications, the strength of this relationship is greatly reduced. This is where Writeback is really valuable! The user entered their specifications and found that there are 1000 sq ft homes priced similarly to 2000 sq ft homes, suggesting there are factors other than size that the buyer should consider, ones which are greatly affecting property valuation. This insight can be shared directly from the platform through the ‘Send Insights to Slack/Email’ button. A powerful insight, revealed and shared seamlessly via the dashboard.

Design choices

Data visualization godfather Edward Tufte introduced the concept of the data-ink ratio: put simply, that data should be visualized using the least amount of ink (or fewest pixels) possible. Designers have to resolve the conflict between optimizing data-ink ratio, and adding supplementary text and annotations to make the data clearer (and nicer-looking).  

This interactive dashboard balances information density with ease of comprehension. The aesthetic was inspired by looking at homes for sale in a newspaper (remember those?), hence the muted color palette, serif font, and column structure. Buying a house is a big decision and the dashboard design reflects this, presenting the information professionally, avoiding garish colors and distracting animations.

Tell your data story with an Astrato interactive dashboard

We’ve explored how Astrato can be used to create interactive dashboards that deliver invaluable insights, are accessible to business users, and match the tone of the subject matter. Writeback and AI-Insights are just two of a host of unique and powerful features offered by Astrato. You can explore similar dashboard examples, like our Google Analytics workbook, here.

 Dashboard creators: Elizabeth Tofany and Piers Batchelor