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Streamlined Essentials: Our Company’s Tech Stack

What is a modern data stack? The Modern Data Stack is a set of technologies, tools, and platforms that are used to extract, store, process, transform, and analyze data in a business context. It includes a variety of cloud-based services, open-source software, and other tools to support activities to process data from raw data to the visualization phase.


Tech Stack
Tech Stack

These cloud-based data warehouses and other tools have been widely used across most organizations due to their effectiveness, efficiency, and cost-saving features. The monthly subscription for these paid tools is very low compared to hardware and onsite data warehouses, which have technological limitations. The Modern Data Stack is designed to enable organizations and businesses to work with data in a more seamless way that allows them to save a lot of time and money and helps the business become more efficient and productive.


Our Data Stack DatumLabs has also designed its own Data Stack, which includes all these tools that make the analysis process faster and more accurate and bring real-time data with minimal maintenance. In this article, DatumLabs has listed some of the tools that are commonly used in its services.

1. Data Extraction

The data is extracted from third-party sources using Airbyte. It’s open-source tools that allow the business to connect to 100+ data sources in its standardized format to further integrate and process.

2. Raw Data Storage

Extracted data is stored in cloud-based data warehouses. In this case, we often use Big Query, which is a cloud-based data warehouse. It allows businesses to store and query a large amount of data in real time.


3. Data Transformation

After storing raw data in Big Query, it is transformed and organized using another open-source tool, i.e., the DBT-Data Build Tool, using SQL. It allows the creation and management of data pipelines in a scalable manner, which makes the transformation part more structured, and useful.

4. Structured Data Storage Transformed data from DBT is stored in Big Query, which makes it easy to query and analyze.

5. Data Visualization Metabase, a BI tool, is used to visualize transformed data by integrating it with Big Query or any other cloud data warehouse. Metabase allows users to create dashboards, reports, and different types of visualization in a user-friendly interface for analyzing data in real-time. This is a quick overview of the entire data life cycle using open-source and cloud-based tools and software, which makes the entire process of data analysis very quick and effective. It enables businesses to get access to their incoming data in real-time to make decisions.


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