From Cron to Modern Data Stack (MDS): Dataflow Automation and Its Current State
The concept that makes the technological miracles of today possible are defined by data. Enormous amounts of data are collected...
Python is great for building web applications but the conventional way of building such apps by using Flask or Django web frameworks involves time-consuming learning for both their development and implementation. Streamlit has simplified web app development using Python and their latest partnership with Snowflake creates more advantages!
Streamlit is a data science and development software that assists data professionals working with data science models or developing applications. Streamlit works as a Python library that you can utilize for building web apps with ease. Almost anyone who can write scripts on Python, and has knowledge of Python fundamentals can use Streamlit.
Building web apps with Django and Flask doesn’t only involve quite a bit of learning but also limits their access to the eyes of data scientists or other members of the data community. Using Streamlit, data analysts, scientists, or hobbyists can build web apps from their machine learning models with a minimal low-code platform like Streamlit.
Snowflake has made a name for the data science industry for its data warehousing capabilities and an array of different analytics stacks. We can say that it is a database software for the cloud which helps companies move from traditional on-premises to seamlessly transition their data architecture into the cloud.
If we look deeper into the system of Snowflake we will notice that from an architectural perspective, what keeps the platform functioning smoothly is the capability to keep computational workloads separated from the storage. One single source of truth brings together two major kinds of data, structured and semi-structured.
Being that Snowflake can be deployed into different cloud providers from AWS to Google Cloud and Microsoft Azure, the vendor lock-in is reduced, opening more ways to work with data. However, there’s an array of other providers that offer an ecosystem of cloud-native data warehouse offerings on these cloud providers which allow you to build and test applications. Something that Snowflake misses but can add to its tool belt is the acquisition of Streamlit framework.
Streamlit CEO and Co-Founder, Adrien Treuille said that “by joining forces with Snowflake, both the Streamlit and Snowflake developer communities will be able to tap into cutting edge technologies for unlocking data’s true potential.”
Snowflake has served as a data platform for many useful data-based applications, such as Lacework or Instacart. But the truth is that not all teams have full-stack engineering teams specialized in building data apps the old way. Therefore, Snowflake envisions the integration with Streamlit will directly empower data scientists and machine learning engineers to create web apps on their own.
Here are four points on which they promise to keep delivering:
It seemed like a no-brainer for the two companies to partner up since they’ve had joint customers who relied on them for their apps. This helps developers and data scientists build these advanced web applications for their needs while working with high-quality standards data that requires little provision and maintenance.
We understand that developing applications for your data insights or analytics needs is challenging. Blue Orange Digital has worked with many organizations to help them build apps or move from on-premises towards cloud environments.
This involves working closely with data platforms like Snowflake (something that’s time-consuming and requires expertise from your staff) and we can assist with the process. Whether you want to build web applications or have other data-related issues, we can help. Simply schedule a free 15-minute call with us here.