Streamlit is a Python library designed for creating data-driven applications quickly and easily that has recently been growing in popularity dramatically. According to Google Trends, more Google searches about Streamlit have been executed now than ever before in Streamlit’s history. Not only is it popular now, but the trend shows that Streamlit is becoming exponentially more used every year. With the immense growth in its popularity, there has never been a better time to start learning Streamlit. Luckily for developers who may have missed out until now, Streamlit’s API is intuitive and mostly well-documented. However, there are some things in Streamlit which can be difficult to understand. One of the most obvious examples is fragments. Fragments are a way for developers to define areas of a Streamlit program which reload independently from the rest of the page. This behavior is very powerful but can also be very confusing. This article will discuss how Streamlit works without fragments, how this behavior changes with the addition of fragments, and how a developer can start using fragments in their Streamlit apps.

In today's data-driven world, organizations are inundated with vast amounts of data from various sources. Every transaction, interaction, and process generates valuable data that, if harnessed correctly, can propel an organization to new heights. While this data holds the potential to provide valuable insights, it can be overwhelming and challenging to interpret in its raw form. This is where data visualization steps in as an indispensable tool for organizations. By converting complex datasets into visual formats such as graphs, charts, and maps, data visualization makes it easier to understand trends, patterns, and outliers. Here’s why data visualization is crucial for any organization.

Python can be a powerful tool for data visualization. It has specific advantages over tools like Power BI and Tableau, such as being easy for programmers and data scientists to learn, access, and integrate into various mediums. There are several popular visualization packages, such as Matplotlib and Plotly, that data enthusiasts can pick up today.

Grant-making organizations are constantly looking for ways to improve their workflows and outcomes. Many organizations use software products like Fluxx to organize their grant award processes with mixed results. While these products are useful, they often lack reporting functions that can provide a more complete view of the organization's grants and where they stand in the process. That's where Moser Data and Analytics experts come in. Our experts can connect your grant-making software data with data from other sources, including survey results, human resources software, accounting software, and more. The results are far-reaching, and will help to optimize your business processes, save time, identify biases, and provide centralized data and reporting. 

Tutorial on how to create a web application on Streamlit using Snowflake and Python.

Snowflake's mission revolves around making data accessible, usable, and valuable to everyone. One of the pillars that have made Snowflake an industry leader is its unwavering commitment to being easy to use and turnkey.

As data-leveraging tools grow more powerful than ever, so has our desire for quick and convenient access to insights. Tableau’s mobile layout feature allows users to quickly reference the data they need regardless of circumstance. Read along for several tips to seamlessly convert your existing Tableau dashboards to a mobile layout in a way that is digestible and powerful for your audience.

The digital landscape of today presents a multitude of data handling platforms and processes, requiring diverse expertise. It's become clear that understanding the division of roles is critical, particularly the distinction between Data Engineers and Database Administrators (DBAs).

Technology has become a central part of modern life. With that has come the availability of Big Data. This blog will explore what Big Data is, where it comes from, how it is used, and why it is important to utilize.

How would a social media app know a user’s google authentication information? After all, google is a separate software and its data is stored separately from that of other applications. The answer is an Application Program Interface (API). APIs are a set of rules and protocols that allow different software programs to communicate and share data. APIs are critical to software and hardware development. In fact, the mouse and keyboard you are using to navigate this blog post are working correctly because of a well-defined API. It’s important for developers and users alike to understand how their various applications work together seamlessly.

Data is everywhere, and that’s not going away any time soon. Learn about data analytics career opportunities and why now is a great time to get started.

Data management is essential for businesses that collect and store data. What processes can you take to keep data safe and useful for your business?

As of Oct 11, 2022 Mainstream Support has ended for SQL Server 2017.

Data management, data analytics, and data analysis… together, they make up the backbone of business, driving optimization, improving workflows, and boosting return on investments.

Companies have more data than they’ve ever had before. Data Management as a Service (DMaaS) can provide teams with a secure solution to data management.

Data equity applies an equity-centered lens and mindset to ensure data is collected, analyzed, interpreted, and shared with diverse stakeholders without bias or exclusion.

The low-code/no-code movement is the next wave of technology innovation.

What is data integrity and why is it important? Since data powers business decisions, it needs to be accurate.

What does democratizing an IT department mean?

A summary of why we want to trust data and the data integrity and data governance practices businesses need.