Aron Clymer, Data Clymer Founder and CEO, and Rob Woollen, Sigma Computing CTO, outline the power of data apps in Part 3 of our “Be a Data Hero” blog series. Tune into their recent Fireside Chat to learn how today’s top data leaders are helping grow their businesses through improved analytics.

Advances in cloud data platforms are now providing a common data infrastructure that empowers companies to innovate on top of their data like never before. With the increase in Data Apps, the data warehouse will evolve from powering traditional business intelligence and internal analytics to powering all the operational applications that run your business.  

Over the course of history, we have seen how improvements in infrastructure lead to more rapid and widespread innovation. A century ago, before the advent of a centralized, reliable electrical grid, any manufacturing company that wanted to build a factory also had to build a power station. So any company building a factory also had to be in the business of power generation. Once electric power was democratized through a national electrical grid, companies could spend more time innovating their products and the pace of innovation accelerated.

A more modern example is Salesforce, one of the first cloud platforms to empower companies to quickly build their own internal applications. Prior to the early 2000s, any company wanting to build a custom software application needed to design and build multiple technical “layers” that were common across all software: data storage, compute resources, security, a graphical user interface, user and application management, application programming interfaces (APIs), etc. Focusing on every layer left a smaller percentage of time and energy to devote to the innovative part: the business logic and user interface that gave end users the features they wanted. Salesforce provided a cloud platform that handled all of those lower-level technical layers so companies could easily build their own custom applications, often without having to write any code. Companies can even sell their applications on Salesforce’s AppExchange.

Now, that same rapid innovation phase is coming to data warehousing. Snowflake’s Data Cloud already has many of the necessary features to make this work, and plenty of vendors are rolling out Data Apps for data users and analysts to consume. And just like Salesforce, Snowflake has created a marketplace where customers can purchase datasets and connected apps.  

So how should your data strategy change to embrace a future with Data Apps? And how can you get started now? We’ll explore all of this in this blog.   

What is a Data App?

Data Apps (sometimes referred to as Connected Apps) are targeted data applications that run directly off a cloud data warehouse (DW). When done right, your DW should be a clean, 360-degree representation of your entire business, normalized and up-to-date. The best way for all of your operational business applications to fully leverage this extremely valuable asset is for them to operate directly on the DW.

This approach eliminates the need for each application to:

  • Maintain its own data storage and processing engine
  • Maintain a partial copy of the entire business dataset
  • Integrate with the DW through data ingestion pipelines and “reverse ETL” pipelines discussed in Part 2 (which are modern day steppingstones to this new future) 
  • Experience data latency because nearly all data pipelines have a lag

The Benefits of Data Apps to Your Business

Some of the benefits that can be realized from moving to Data Apps to run your business include:

  • Realize the full value of your data: Data Apps enable organizations to activate and operate on data where it lives in the DW. Thus, your business can take action on data as soon as it appears, maximizing the business impact.
  • Faster value: The more data apps you are using, the less need to build and maintain data pipelines. This reduces the time to implement an automated data-driven business process.
  • Enable data democratization: Up-to-date data can now be made available to all data consumers of a specific application vs. those who might only have visibility to an executive dashboard. This empowers these users with the right information they need in order to be successful in their roles.
  • Reduce costs: Because the system is simplified with this approach, costs to build and operate the system come down.

What are the top Data Apps?

Sigma Computing was one of the first Data Apps on the market. It is a full-cloud data analytics solution that operates directly on top of your DW to give end users instant access to all of the latest data. It has a familiar spreadsheet interface that empowers users to explore, analyze, visualize, collaborate, and operate on their data in a self-service way with no technical skills required. Sigma makes it easy to activate your data with features like automated dashboards, alerts, and even writing back results to your DW, which can then be consumed by other complimentary Data Apps. It also has robust embedding capabilities that make it easy to develop Data Apps directly on top of your data, allowing flexibility in presentation, exploration, and customization.

Flywheel Software is another example of a Data App. Flywheel allows non-technical marketers to easily create audiences, run campaigns, A/B test results, and even incorporate AI and predictive modeling to optimize audience engagement. And, because Flywheel operates directly on top of your DW customer records, it can instantly and seamlessly take advantage of all the investment you’ve made into consolidating, de-duplicating, cleaning, augmenting, and decorating the 360-view of the customer through your data modeling efforts. As soon as a new customer attribute is added to the DW, marketers can immediately incorporate it using Flywheel.

Snowflake, a recognized leader in the space, is paving the way for Data Apps with features like:

  • Unistore: This enables users to build transactional apps directly on Snowflake, run real-time analytical queries on transactional data, and get a unified approach to governance and security. 
  • Snowpark: The Snowpark library provides an intuitive API for querying and processing data in a data pipeline. Using this library, you can build applications that process data in Snowflake without moving data to the system where your application code runs (including Python).
  • Streamlit: This is a pure-Python open-source application framework that enables developers to quickly and easily write data applications.
  • Snowflake Marketplace: Discover, evaluate, and purchase connected applications.

Real-World Examples

MineralTree is an Accounts Payable (AP) and payment automation solution provider that used Sigma to build MineralTree Analytics: a data app solution that integrates with their customers’ financial systems and provides comprehensive visibility into every aspect of the AP process. It enables users to escape the confines of spreadsheets and start independently exploring their data through rich KPI visualizations that help surface insights and make data more actionable.

Another real-world example of the future of a modern cloud DW solution is illustrated by the partnership between Data Clymer and The Big Ten Conference. Data Clymer has designed a data app solution architecture to fulfill The Big Ten’s vision to set the standard for sports data analytics and revolutionize how universities, conferences, and sports organizations (across all levels) engage with their fans—improving overall fan experience and fan revenue.  The Big Ten is running Sigma and Flywheel on Snowflake’s Data Cloud.

The Culmination of the Data Hero’s Journey

In Part 1 of our “Be a Data Hero” series, we focused on five best practices for today’s data and analytics journey. In Part 2, we discussed the next evolution in activating your DW data by building “reverse ETL” data pipelines that copy master data back to operational applications (aka, operational analytics). To wrap up our journey, we explored Data Apps and how they can benefit your business.

Ready to Continue Your Data Journey?

If you have a cloud data warehouse but are struggling with how to best accelerate your data journey, our team at Data Clymer can help! We have helped many organizations like the Las Vegas Raiders, Kentik, and the Big Ten Conference advance their data strategies and operationalize their data to better understand their customers and their business.

Contact us or send an email to to learn more about how our team can help you become a data hero.

Further reading:

Aron Clymer

About the Authors

Aron Clymer, Founder and CEO, Data Clymer

An executive leader passionate about extracting maximum value from data, Aron founded Data Clymer to help organizations implement optimal data strategies and instill a data-driven culture. With over two decades of experience, he more recently spent seven years building and leading the Product Intelligence team at Salesforce, and another two years doing the same at PopSugar.

Rpb Woollen, Sigma Computing

Rob Woollen, Co-Founder and CTO, Sigma Computing

Rob has over 20 years of experience building distributed and cloud systems. He spent 6 years at serving as the CTO for the Salesforce Platform and and Sr Vice President, Platform Product Management. Rob holds a Bachelor of Science degree in Computer Science from Princeton University.