Open source Modern Data Stack for the financial industry

The open source Modern Data Stack (MDS) is a solution that offers reduced costs, flexibility and enhanced security for the financial sector. 

In a market where efficiency and control over data are essential, it is important to find an approach that balances cost-effectiveness and robustness. 

In this blog post, we'll explore how this emerging technology can transform data management in financial institutions.

Read on to discover the main advantages, how to implement open source MDS and why it's the right choice for your company. 

Firstly, what is Modern Data Stack (MDS)?

The Modern Data Stack (MDS) is Indicium's methodology for creating data platforms with governance, agility, and efficiency. 

Bringing together people, processes, and tools, the MDS is part of a culture that companies must build if they want to transform data into accessible and actionable assets, driving the evolution of all business areas. 

Its principles are: 

1. Cloud storage 

In the Modern Data Stack, data is stored centrally in the cloud. This is a highly scalable and flexible technology, which makes it easier to process big data quickly and securely. 

One of its biggest advantages is the reduction in infrastructure, installation and maintenance costs. 

2. Modularity 

Modularity in data is the practice of structuring a data system into independent components or modules, each responsible for a specific function or part of the data.

This approach facilitates system maintenance, development, and scalability, allowing each module to be changed or updated without negatively impacting the others.

3. Simplicity 

The idea behind the Modern Data Stack is that highly complex processes are handled by the tools, while the user interface remains as simple as possible. 

For this reason, data transformation is performed centrally using SQL and Python, which brings benefits such as democratizing information and reducing maintenance and training costs.

4. Governance 

Through data governance practices, information is centralized and easily accessible in one place, simplifying documentation. 

This makes it possible to create permissioning logics and manage sensitive data in an integrated way, bringing greater security and ease to the day-to-day use of data in the company. 

5. Versioning 

Versioning is the practice of tracking and managing different versions of a file, code, document, or dataset over time. 

This allows you to keep a detailed history of changes, making it easier to restore previous versions, compare changes, and enable teamwork on data projects. 

6. DataOps

DataOps is the modern approach to managing data efficiently and collaboratively, aligning data operations with business needs. 

It combines practices, processes, and tools to improve efficiency, quality, and reliability throughout the data lifecycle—from ingestion to analysis andinsights. 

It thus aims to bring automation, collaboration, and continuous integration to data management.

Check out the main differences between the modern and traditional models below. 

Modern Data Stack vs. Traditional Data Stack

The Modern Data Stack and the Traditional Data Stack represent different approaches to data management and processing, reflecting technological evolution and business needs. 

The Traditional Data Stack is based on local infrastructures, with traditional ETL systems, centralized data warehouses, and a monolithic architecture, which are difficult to scale and update.

In this model, data is usually stored on dedicated physical servers, located within the organization itself or in third-party data centers—but still under direct management. 

In contrast, the Modern Data Stack is cloud-native, leveraging managed services, ELT tools, and cloud data warehouses along with a modular and flexible architecture. 

It offers almost unlimited scalability, agile implementation, usage-based costs, and distributed governance, making it better suited for today's challenges, where flexibility and innovation are essential.

The Modern Data Stack architecture

As you have already seen, the main feature of the Modern Data Stack architecture is its reliance on cloud computing, which provides scalability and flexibility. 

Beyond that, this architecture starts with data ingestion, during which various integration tools capture data from a wide range of sources, including databases, APIs, and SaaS systems. 

This data is moved to cloud data warehouses, such as Snowflake, BigQuery, or Amazon Redshift, which serve as central repositories. 

These data warehouses are designed to handle large volumes of data and offer high processing capacities, allowing them to be consolidated and stored in a single environment.

Once the data is stored, the Modern Data Stack architecture facilitates transformation and modeling using tools such as dbt (data build tool). 

This process transforms raw data directly within the data warehouse and prepares it for analysis and reporting. 

The MDS architecture also involves data visualization and analysis, using business intelligence (BI) platforms, which connect easily to data warehouses in the cloud.

This allows data teams to create interactive dashboards and dynamic reports that can be shared throughout the organization, making the  data-driven decision-making process even more agile and informed. 

The modularity of this architecture allows new tools to be easily integrated and the infrastructure to evolve as needed, maintaining continuous efficiency and innovation.

See below how all this can be useful for financial services. 

Open source Modern Data Stack for the financial industry

The open source Modern Data Stack (MDS) is a solution that offers reduced costs, flexibility and enhanced security for the financial sector. 

It is an emerging approach that combines various open source tools to build a robust and scalable data pipeline, with the aim of improving data analysis and management in business environments.

Its main advantages are: 

• Cost: open source tools are generally free to use—though there might be costs associated with infrastructure, support, and maintenance.
• Flexibility and control: you can customize and adjust the tools according to your specific needs. Open source allows for user modifications and contributions.
• Community and support: help comes mainly from the community of users and developers—but some companies offer paid support for open source tools.
• Integration: many open source tools are designed to be easily integrated with other open source solutions, providing a modular and customizable approach.
• Transparency: the source code is accessible, which allows users to understand how the tools work, ensuring that they meet security and privacy requirements.

The open source Modern Data Stack is an excellent solution for financial services, especially in terms of cost and flexibility. 

Take a look at some of the companies in the industry that already leverage this resource in parts of their pipeline: 

• BV Bank
• Edenred 
• Stellar
• Q2 bank
• Itaú Foundation
• Unibanco Institute

With open source tools, financial institutions can significantly reduce licensing costs and customize solutions specific to their needs, such as regulatory compliance and legacy system integration.

The transparency of open source software allows for greater control and compliance with security and privacy standards.

The scalability of open source tools is also crucial to handle large volumes of data and meet growing demands. 

The active community drives innovation and agility, by providing rapid updates and technical support, which enables organizations to adapt quickly to changes in the financial sector.

The flexibility of the open source Modern Data Stack also makes it easier to implement customized security measures and adapt to specific regulations, such as data protection laws and other local standards. 

With less dependence on external suppliers, institutions retain full control over their data and processes, reducing risks associated with price fluctuations and support changes.

Interested in knowing how to build your own modern data platform? 

Click here to access Indicium's free blueprint and learn everything you need to know about the Modern Data Stack.