Building business data visualization applications with Streamlit and AI

The growing need for data visualization in businesses

Today, businesses are inundated with data. Whether it's key performance indicators (KPIs), sales data, customer information, or financial forecasts, business leaders need to have a clear, real-time view of their business. The challenge often lies in transforming this mass of raw information into actionable insights that are easy to understand and share.

Let's take a simple example. Imagine a retail company: sales, inventory, delivery and forecast data must be available clearly and accurately for managers and managers. Without an intuitive interface to consult this information, making quick and effective decisions becomes a challenge. Teams then find themselves analyzing endless Excel files or waiting for reports from a complex IT system, which hampers their responsiveness.

That's where data visualization comes in. Interactive dashboards, dynamic charts, and intuitive interfaces can make data accessible to everyone, not just technical experts. They make it possible to transform complex data into clear visualizations, allowing decision makers to make faster and more informed decisions.

Why is it crucial for directors and executives?
Because better informed decisions make it possible to optimize business performance, identify trends earlier, and respond more quickly to market changes. That means less time spent analyzing scattered data and more time spent acting on hard facts.

‍

Streamlit: an asset for your data teams

Faced with this growing need, tools like Streamlit have established themselves as ideal solutions for easily creating interactive data visualization applications. But why Streamlit in particular?

The strength of Streamlit lies in its ease of use. It allows your data teams — who already know tools like Python — to quickly transform their analyses into interactive applications. This means that, even without an IT team dedicated to application development, you can easily deploy dashboards and visualizations to track your key metrics.

Streamlit allows you to switch from spreadsheets to dynamic dashboards in a few lines of code. In other words, your data teams can take raw data, create an interactive dashboard prototype, and share it with managers or directors, all in the same day. What would usually take weeks of development and require several meetings with technical teams is becoming a much smoother and faster process.

One of the great advantages of Streamlit, is that it allows translate complex data into visual interfaces that everyone can understand, without the need to understand the code behind it. Let's take an example: a sales team might need to monitor the performance of its salespeople and flagship products in real time. In a few hours, a Streamlit application could be set up to display interactive charts and dashboards that are updated every time the data is updated.

‍

‍

What are the benefits for managers?

• Increased autonomy of data teams : thanks to Streamlit, your teams can quickly develop tailor-made solutions without going through long and expensive development cycles.
• Faster decision making : with visualizations available in real time, you have a clear overview, allowing you to adjust your strategies based on the most recent data.
• IT cost reduction : Streamlit simplifies the development of interactive applications, allowing you to deploy tools in-house without having to invest heavily in development resources.

In summaryStreamlit makes it possible to meet the visualization needs of businesses by offering a fast, flexible and adapted tool for teams that are already familiar with data analysis. It is a strategic asset for any organization looking to maximize the impact of its data and improve collaboration between its teams.

‍

AI: an accelerator for the creation of interactive applications

In addition to the simplicity provided by Streamlit, it is possible to go even further by integrating artificial intelligence tools, such as GPT chat, to facilitate and accelerate the creation of interactive applications. If your data teams are proficient in Python, they can sometimes encounter bottlenecks or repetitive tasks that slow down the development process. AI intervenes here as a real assistant, by automating certain tasks and by offering quick solutions.

Let's take a concrete example. Imagine that your data team is developing a dashboard to track the performance of multiple departments. She may encounter code errors or need to optimize certain visualizations. Instead of wasting time looking for solutions in documentation or online, AI, using tools like ChatGPT, can directly suggest code corrections, better alternatives, or even generate custom code segments.

How does AI speed up the creation of applications?

• Code generation : AI can offer custom code blocks, adapted to the specific needs of the company. For example, if you want to show a specific visualization, ChatGPT can suggest the corresponding code, saving valuable time for your teams.
• Optimization and correction : AI can also help correct errors in code, or suggest improvements to make applications more efficient and responsive. This reduces the risk of bugs and improves the overall quality of dashboards.
• Automating repetitive tasks : Some tasks, such as generating interactive forms or updating data, can be tedious. Thanks to AI, these steps can be automated, freeing up time for your teams.

Concretely, what are the benefits for decision-makers?

• Considerable time savings : Data teams can spend less time on repetitive or technical tasks, and focus more on creating high-value applications.
• Reduction of errors : AI suggests corrections and optimizations in real time, which helps to ensure better quality applications.
• Improving the autonomy of teams : Even team members with less development experience can use AI to move forward more quickly, reducing dependence on external resources or specialized developers.

By integrating AI into your development processes, you create an environment where your teams can quickly transform data into interactive applications, while increasing efficiency. This results in better, faster, and more reliable decision-making, which is an essential asset for any business that wants to remain competitive.

‍

Other frameworks for creating interactive applications: an alternative for specific needs

Although Streamlit is an ideal solution for many businesses thanks to its simplicity and speed of deployment, there are other frameworks adapted to more specific needs. Depending on the size of your business, the complexity of your data and the skills of your teams, tools like Dash, Panel, There you go and Shiny may be good alternatives to consider.

Dash

Dash, developed by Plotly, is another open-source framework that allows you to create interactive web applications using Python. It is particularly popular for complex data visualizations or interfaces that require a high level of customization. Unlike Streamlit, Dash can offer more flexibility if your technical teams have specific design or feature needs.

When should I use Dash?

• If your teams need to develop custom applications with finer control over graphical and interactive elements.
• If you have complex data that requires more advanced visualizations.

Panel

Panel is another open-source framework, which, like Streamlit, allows you to create interactive applications with Python. It offers seamless integration with popular libraries like Bokeh, HoloViews, and Matplotlib, making it a great choice for businesses looking to take visual data analytics a step further. Panel is distinguished by its ability to support more complex dashboards.

When should I use Panel?

• If your teams are already working with visualization libraries like Bokeh or HoloViews.
• If you need increased flexibility for dashboards with lots of simultaneous visualizations.

There you go

There you go turns Jupyter notebooks into interactive web applications. If your teams already use notebooks to analyze and process data, Voilà can be an ideal solution for sharing these analyses in the form of interactive applications. This allows interfaces to be created without additional development effort.

When should you use Voilà?

• If your teams work primarily with Jupyter notebooks for data science.
• If you need to quickly share analytics in the form of applications without rethinking the existing workflow.

Shiny

Shiny, on the other hand, is a framework designed for R, which allows you to create interactive web applications with sophisticated visualizations. It is ideal for companies that have teams using the R language, which is very common in the field of statistics and data science.

When should I use Shiny?

• If your teams primarily use R for data analysis.
• If you need interactive applications with complex visualizations and statistical processing.

‍

These frameworks offer solid solutions for specific needs, but Streamlit is often the easiest and quickest option to deploy. Adopting it does not require a heavy investment in technical skills, making it more accessible to a wide variety of businesses. However, if your needs are more complex, Dash, Panel, Panel, Voilà, and Shiny can be interesting alternatives to complete your technological toolbox.

‍

Concrete benefits for your business

When you adopt tools like Streamlit, in combination with artificial intelligence technologies, the benefits for your business go well beyond simple data visualization. Indeed, this combination of tools allows you to deeply transform your decision-making processes, by making data analysis more accessible and faster for all employees. But what does that mean in practice for you, as a business leader?

1. ‍Time and efficiency savings : instead of spending hours or even days preparing reports or analyzing data via complex Excel tables, your teams can develop interactive applications in real time. This not only saves time but also makes decision making a lot smoother.
   Let's take the example of a company that needs to track the performance of its direct sales. With Streamlit, she can set up an application that is automatically updated with each new transaction, offering a real-time view of the sales team's results. This type of automation allows managers to focus on analysis and strategy, rather than collecting and organizing data.
   ‍‍
2. Autonomy and strengthened collaboration : by making tools for visualizing and creating applications accessible to your data teams, you reduce dependence on an IT team or external developers. This means that your collaborators can create, adjust and share their own dashboards according to the specific needs of their departments.
   In addition, the implementation of these tools promotes better collaboration between departments. Teams can easily share visualizations with other departments, allowing everyone in the organization, from analysts to directors, to rely on clear, up-to-date data to make concerted decisions.‍
   ‍
3. Cost reduction : one of the direct benefits of using Streamlit and AI is the reduction of costs associated with developing custom applications. Instead of having to mobilize a development team to create custom interfaces, your teams can build their own tools without the need to go through a long and expensive process.
   It also means that you can respond more quickly to opportunities and challenges of the market. By reducing the time it takes to implement data-driven solutions, your business can remain more agile and responsive.
   ‍‍
4. Better decision making : interactive applications and clear data visualizations allow managers to have an accurate overview of the situation of their business. By offering simplified access to Key KPIs and metrics, Streamlit and AI allow you to quickly adjust your strategies and actions according to market needs.
   For example, in the context of an economic crisis or a rapid change in consumer preferences, you can rely on visualizations that are updated in real time to respond more effectively. This gives you an undeniable competitive advantage in an increasingly uncertain and fast-paced business environment.

‍

So why adopt Streamlit and AI in your data strategy?

In a world where the Data has become a crucial resource for decision-making, it is imperative for companies to equip themselves with the right tools to exploit this wealth of information. Solutions like Streamlit, coupled with artificial intelligence, are not only trendy technologies, they meet real strategic needs: save time, optimize costs, and enable informed decision-making.

Streamlit is distinguished by its ability to democratizing access to interactive data visualizations, even for non-technical teams, while reducing development time and costs. Combined with AI, this solution becomes a powerful lever to accelerate the digital transformation of your company and make your teams more autonomous.

For a company manager or executive, the benefits of these technologies are clear:

• You allow your teams to create custom tools without depending on expensive IT resources.
• You have up-to-date data in real time to make faster and better informed decisions.
• You stay nimble and able to respond to market challenges and opportunities with greater efficiency.

If you want your business to be at the forefront of innovation and for your teams to be more autonomous in their data management, it's time to consider adopting Streamlit and AI. These tools will allow you to get the most out of your data while speeding up your internal processes. The next step? Explore these solutions and see how they can transform your organization today.

‍

‍