4 Key Components of The Modern Data Stack

Modern Data Stack Showcase

Pandera’s very own Director of Data Services Daniel Zagales joined Cade Winter from Fivetran and Bruce Sandell from Looker for a showcase of The Modern Data Stack (MDS). This virtual event held in February of 2022 aimed to highlight each technology and its position in the stack. 

In its simplest form, a MDS only requires an ingestion tool, a warehousing tool, a transformation tool, and a business intelligence tool. Let’s look at what a Modern Data Stack is and see why organizations are utilizing it for successful business outcomes.

An Overview of the Modern Data Stack

Essentially, the Modern Data Stack consists of a flexible set of technologies that help businesses store, manage, and learn from their data. It lowers the technical complexity of entry for data integration in an organization. 

“The Modern Data Stack brings enterprise-grade systems to a larger consumer base,” Daniel mentioned during the showcase.

A MDS includes a fully-managed data pipeline for “extract, load, and transform” (ELT) processes along with a cloud-based data lake or warehouse for the data’s storage. On top of that, MDS requires a data transformation tool and business intelligence (BI) platform so your company can visualize and act upon the data.

The Modern Data Stack

These tools aren’t new, as anyone who has worked with data and analytics is fully aware. Yet what makes a data stack “modern” is its ability to meet the data demands of today caused by obstacles during the data’s lifecycle.

There are many reasons that successful data-driven organizations are utilizing a MDS. In particular, the benefits of this data stack include:

  • High operational and execution speeds
  • Cost-effectiveness
  • Scalability
  • Avoiding vendor lock-in 

With those benefits, teams are able to make better data-backed decisions and continue to innovate. As Daniel Zagales put it, “implementing a Modern Data Stack is just the start, its true power comes when you activate it.”

Given that there are so many layers to a MDS, here’s a look into what the components of one are.

Data Integration

Data integration plays a major role in the Modern Data Stack. After all, it is the process of collecting data from different sources to be stored in a medium like a data warehouse. It’s common for organizations to have multiple data sources, which stream into a common data warehouse or data lake.

An example of a data integration platform is the Fivetran platform. Fivetran ensures reliable data access, and accelerates analytics with ready-to-query schemas and managed in-warehouse transformations.

Data Storage

This is where all the data coming in from the data sources is aggregated and stored. In the context of a MDS, data storage refers to a cloud-based solution, like a data warehouse or data lake, where your data ingestion tool will send your data.

One of the major modern data warehouses is Google Cloud’s BigQuery, which is a serverless, multi-cloud solution that helps organizations manage their big data easily.

Data Transformation

Data transformation is the process of converting data from one format to another, typically from the format of a source system to the format of the destination system. Data transformation tools also make it possible for different types of data to work together. Obviously, with multiple data sources, this is an important component of the Modern Data Stack.

Data Visualization / Data Analytics

It may sound self-explanatory, but data visualization is a key component of the Modern Data Stack, allowing users to explore insights to then take action upon.

In the past, business intelligence (BI) and data visualization solutions were initially designed to build reports and dashboards. Yet as big data and analytics continue to evolve and become more essential to business goals and objectives, the need to go beyond simple BI solutions is evident.

As part of Google Cloud, Looker is a modern BI platform that provides not just dashboards, but other benefits such as:

  • An API-first and cloud-native platform for integrating into existing workflows
  • Semantic modeling layer for enterprise-wide governance 
  • In-database architecture for access to real-time data

Remember, data without activation is just information. Upgrading to a Modern Data Stack allows organizations to concentrate on analytics rather than data engineering.

The Modern Data Stack for Your Organization

The Modern Data Stack is a necessary evolution of the rapid pace of changes in the data world. And, it’s not just for enterprise organizations who had the funds to upgrade. 

Businesses of all sizes can benefit from a powerful technology stack with components that are agile, flexible, scalable, and built-to-last for the ever-evolving technology landscape. As Daniel put it during his presentation, “you have to meet your end-users in the tools they do business in.”

A major problem with organizations trying to modernize their data stack is making sense of what combination of tools to choose. There are many to choose from, and it is overwhelming trying to decipher which may be the right choice. 

Whatever choices that organizations make, it also takes time to integrate each tool and work through issues that may arise. Thankfully, Pandera is here to assist.

Pandera works alongside organizations to assist them on their journeys to upgrading to a Modern Data Stack. Our data experts understand that for a successful MDS, each layer must work together to truly unlock full value.

If you would like to learn more about what a Modern Data Stack can do for your organization and how Pandera can assist, please reach out to us today!

Learn more about our Data Warehouse Modernization services.