Data Engineering & Architecture

The foundational cornerstone of every data analytics solution.

Why Data Engineering & Architecture?

Organizations increasingly demand data to help them make better decisions. Data Engineering & Architecture enables meeting these demands.

A solid data architecture is built on robust engineering processes. The Data Engineering & Architecture stage is critical, accounting for 80% of the time spent on data & AI projects. Any analysis based on improperly processed data will lead to more errors, which is why it is so crucial.

At Datalytics, we develop and optimize architectures to ensure they are scalable, cost-effective, and deliver real business value.

0 %

believe that a solid data architecture is crucial for continuous innovation.

Source: Deloitte

0 %

reduction in the time to access business insights.

Source: IDC

0 %

of AI projects depend on data engineering infrastructure.

Source: WEF

Our approach

Datalytics’ Data Engineering & Architecture services offer the following key differentiators:

Expert Know-How

Our team includes certified professionals in the latest market technologies (Databricks, Azure, AWS, dbt, etc.). We stay up-to-date with the newest advancements to ensure your architecture is as efficient as possible.

Control throughout the entire data lifecycle

We work on every stage of your data lifecycle, from collection to integration and management. By automating and streamlining data collection, we ensure consistency across all your information.

We integrate AI

We research the latest AI advancements and apply them to make the work more effective. We develop intelligent agents that help optimize your data engineering processes (such as migrations, code reviews, etc.).

Expert Know-How

Control throughout the entire data lifecycle

We work on every stage of your data lifecycle, from collection to integration and management. By automating and streamlining data collection, we ensure consistency across all your information.

We integrate AI

Our clients

Client testimonials

Working with Datalytics has been an incredibly fruitful and enriching experience. The high standards of quality, service, creativity, and teamwork at Datalytics have allowed us to develop great solutions and innovations. Perhaps the most representative of these is the biosciences bot, an AI tool that enables us to access our genetic information quickly. What once could take months, we now do in seconds, and thanks to that, we can deliver diagnostic solutions much more efficiently to our patients. This tool has been nationally and internationally recognized as a major development in the field of AI in genomics.

Carlos Agudelo Biosciences Manager at Sura

Datalytics has allowed us to develop valuable data utilization capabilities within the organization, enabling us to leverage initiatives and support different processes with relevant and timely information. With the technical excellence of their professionals, the application of best practices, and their clear focus on results, they have given us great confidence when facing the challenges we have and the key projects that bring us closer to our higher purpose: helping businesses and institutions in the region grow.

Santiago Galeano Cadavid Head of Analytics at the Chamber of Commerce of Medellín for Antioquia

We are very pleased with the experience we've had with the Maxi chatbot that we developed together with Datalytics. With the generative AI tools available to us (Azure OpenAI), we were able to enhance it and make it understand corporate processes to handle inquiries from different areas of the organization. This speeds up many queries that would normally take a business day; now we resolve them much faster with Maxi. This has saved us a lot of time in terms of productivity, and we're very happy because the bot is now being used in more companies within the group, which makes our technology team very proud.

Aaron González Digital CoE LATAM at ISA Intercolombia

At Datalytics, they are experts in data engineering. They helped us guide the development very clearly, meeting deadlines and project scope. They also provided valuable recommendations based on the situation of our company.

León Buitrago López Analytics and Business Intelligence Coordinator at Coninsa

Frequently asked questions

What is Data Architecture?

Data Architecture is a combination of technologies that enables organizations to address their information needs. For example: how much was sold, how many customers were gained or are at risk of being lost, what the stock level of products is, etc. It provides all the data the business needs to make data-driven decisions.

Why is Data Engineering important?

Data Engineering is crucial because it is the discipline responsible for obtaining, cleaning, integrating, and enriching data to enable any type of subsequent analysis. Without robust data engineering processes, a data-driven culture cannot exist.

What business needs can Data Engineering & Architecture address?

Data Engineering & Architecture solutions allow organizations to have a single repository of information—whether a data warehouse, data lake, or medallion architecture—to unify the truth across the company, making it easier to make data-driven decisions.

These solutions make it possible to provide the business with data from structured sources (databases, spreadsheets, ERP, CRM, etc.) and unstructured sources (videos, images, social media comments, etc.), process data in real-time, automate data collection processes to save time, resources, and manual tasks, among other benefits.

Is a defined technology necessary to build a Data Architecture?

Not necessarily. At Datalytics, we adapt to our clients' technology stack. If they don’t yet have one defined, we help them select the most suitable technology based on their needs and budget.