Core Components of the Modern Data Stack

The digital age has allowed for more innovation and forward progress in commerce and business than at any other time throughout history. With technology evolving and becoming more and more accessible, the worldwide market keeps growing and growing. For any business, from the biggest corporations down to the startups that just began operations, data is one of the most important factors. 

Data has always been at the heart of what has helped businesses grow and industries surge forward, and in the digital age, it’s no different. One of the biggest challenges that the digital age has brought with it has actually been finding ways to utilize and activate the massive amount of data that is constantly being generated. Digital data is a ubiquitous part of the business world and companies and industries have to find ways to not only understand it but use it.

This is challenging because there are so many ways that data is created and not only that but it is created at an incredible rate. Thankfully there is a solution to this challenge, and it’s the modern data stack. Without the modern data stack, it would be incredibly hard if not impossible to actually activate and use data across a company. Without data, growth, expansion, and analytics wouldn’t exist as they do. 

If you have been curious about what the core components of the modern data stack are, and why they are so important, here is everything you need to know! 

Out of the Silos

The data stack has been around for a long time and is no ‘new’ concept, however, there is a significance to what makes a ‘modern’ data stack actually modern. The problem of data that is either hard or impossible to interact with is known as a data silo. For businesses that don’t have competent data stacks in place, their data exists in a silo where it is just out of reach. Yes, they are creating it, but it’s not available for analytics, or operationalization in any kind of way.

The original solution to this was what is known as a traditional data stack, or an on-premise data stack. These were tools that took data and aggregated them to a physical location, like a server. Using tools like ETL, which stand for Extract, Transform, and Load, these systems would take data from disparate sources and put them in one centralized location. This location became known as a data warehouse. Now, instead of having scattered, unified data, companies had access to one source of truth that could stretch across their company. 

Into the Modern Era  

As time went on and technology advanced, the ability to create cloud-based data warehouses became not only popular but mainstream. Snowflake became one of the most popular cloud-based data warehouse providers on the market and this helped lead into the modern era.

Having a cloud-based over on-premise system helped to free up businesses in a lot of creative, and productive ways.

Now developers could create tools that utilize different methods of data aggregation like ELT which transforms data once it’s actually loaded into the warehouse. This opened up a lot of opportunities for data engineers and developers to create tools that helped to cut costs and drive the industry forward.

Reverse ETL is an example of how the modern data stack has empowered real innovation that is changing business. Even though the modern data stack created a lot of opportunities for improvement over the traditional, the issue of data activation is still very much real. Data activation is the ability for a company to not only aggregate their data but use it in real-time. Often times data is used for retroactive analysis, which does have its place and can be a powerful tool. However, being able to give leaders and departments across a cross-company the data they need in real-time to make data-driven decisions is a challenge.

That’s where reverse ETL comes into the picture as an option to help activate data and power data operationalization in meaningful ways. By pushing data back out to endpoints through reverse ETL, you allow for data enrichment, automation, and activation giving departments data in real-time. 

Core Components

The modern data stack utilizes cloud-based technology to promote simplicity, speed, and scalability. These are the core components that every good data stack will have:

• Data Acquisition
• Event Tracking
• Data Integration

These three components cover the foundational aspects of what makes a modern data stack effective. Acquiring data from disparate sources, capturing and collecting behavioral information from events, then integrating that data into use throughout your company.

Conclusion

The modern data stack has come a long way and continues to improve. As technology evolves there will always be more creative and effective ways of not only capturing data but utilizing it to help drive industries forward.