Data Architecture

The Blueprint For Data Success

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Illustration depicting 'Data Architecture' with two people interacting with a large interconnected network diagram containing nodes and icons such as a cloud, dollar sign, and charts. The dark background with blue and white accents highlights the concept of structuring data systems.

Good Data architecture provides seamless capabilities across every step of the data lifecycle and undercurrents.

Data architecture is the design of systems to support the evolving data needs of an enterprise, achieved by flexible and reversible decisions reached through a careful evaluation of trade-offs.

Getting confused between with the buzzword hype between

data mesh, data lake, data lakehouse, etc.?

Inaccurate data and latency to load the

dashboards have become standards?

Inaccurate data and latency to load the

dashboards have become standards?

Not sure if you need a batch or a streaming system?

Your dashboards are hard to

understand and you can’t get

the insights you need in seconds?

Your dashboards are hard to understand and you

can’t get the insights you need in seconds?

Will your data architecture support your

organization's long-term data strategy and goals?

Will your data architecture support your

organization's long-term data strategy and goals?

Will your data architecture support

your organization's long-term data

strategy and goals?

Solutions

Architectures and blueprints in line with the overall business strategy

Data is not an isolated component, and as it is transversal to all departments, we take a holistic approach when tackling data architecture. We make sure to understand the current IT footprint at the company level as well as the different data needs and desires of each department. We then draft a concrete blueprint with clear arguments for each architectural decision.

Align with Global Data Strategy

Illustration of a pyramid divided into four layers: 'Business Strategy' at the top, followed by 'Data Strategy,' 'Data Architecture' highlighted in blue, and 'Data & Technology Implementation' at the base. The diagram emphasizes the hierarchical relationship between business strategy and its foundational layers, set against a dark background with white and blue accents.

Diagram illustrating 'Data Architecture' with two labeled boxes: 'Operational' with the subtitle 'What' and 'Technical' with the subtitle 'How.' The simple layout highlights the dual focus of data architecture, presented on a white background with a dark border.

Operational and Technical data architecture

Operational architecture encompasses the functional requirements related to people, processes, and technology. Technical architecture outlines how data is ingested, stored, transformed, and served along the data lifecycle. We know the importance of grasping the “what” well before thinking and executing with the “how”.

The Right Structure for Your Data

Data Lakes, Data Warehouse, Data Lakehouse, Medallion architecture, etc. have a lot of literature and fuzz around them that makes it overwhelming to choose the right one. We help you cut through the noise and choose the right solution for your needs, whether it's a data lake for flexibility, a data warehouse for analytics, or a data lakehouse for a combined approach.

Illustration comparing 'Data Lake,' 'Data Warehouse,' and 'Data Lakehouse' with visual metaphors: a circle resembling a lake for 'Data Lake,' a building with a garage door for 'Data Warehouse,' and an A-frame house for 'Data Lakehouse,' all filled with binary code patterns. The 'VS' labels highlight the distinctions between these concepts, set against a dark background with blue and white accents.

Illustration representing a 'Data Mesh' concept with interconnected cubes linked by lines, surrounding a layered, stacked structure at the center. The design symbolizes decentralized and interconnected data nodes, emphasizing the distributed nature of data ownership and architecture, set against a dark background with blue and white highlights.

Data Mesh in mind

Data mesh is an emerging paradigm that offers a decentralized and domain-driven approach to data architecture. We help you explore the potential of data mesh for your organization, assess its suitability, and guide you through the implementation process. Our experts can help you design a data mesh architecture that empowers domain teams, promotes data ownership, and unlocks the full value of your data.

Batch and streaming paradigms

We help you navigate the complexities of batch and streaming data processing, including advanced architectures like Kappa and Lambda. Whether you need to analyze historical trends or respond to real-time events, our experts can design and implement solutions that deliver timely and accurate data to your business. We consider factors such as data volume, velocity, latency requirements, and business needs to recommend the most suitable architecture for your specific use case.

Illustration representing the decision-making process between 'Real-Time' and 'Batch-Based' paradigms. It features a person in a thinking pose with speech bubbles containing the two options, symbolizing the choice between streaming and batch data processing. The design uses a dark background with blue and white highlights to emphasize the contrasting paradigms.

Our Architecture Principles

Select foundational technologies that promote interoperability, maintainability, and scalability across your systems.

Choose common components wisely

Design systems that can gracefully handle failures and recover quickly to minimize disruptions.

Plan for failure

Build systems that can handle increasing data volumes, user traffic, and business demands without compromising performance.

Architect for scalability

Guide and influence technology choices to align with business goals and drive innovation.

Architecture is leadership

Continuously evaluate and evolve your architecture to adapt to changing needs and technological advancements.

Always be architecting

Design modular components with minimal dependencies to increase flexibility and maintainability.

Build loosely coupled systems

Choose architectural approaches that allow for easy rollback or modification if needed.

Make reversible decisions

Embed security considerations into every architectural decision to protect sensitive data and systems.

Prioritize security

Optimize cloud costs by designing efficient architectures and adopting cost-conscious practices.

Embrace FinOps

Why us

Choosing the right partner for data architecture topics is a critical choice as those

decisions will have long-lasting impacts.

We are convinced to be a strong partner for the following reasons:

Choosing the right partner for data architecture topics is a critical choice as those

decisions will have long-lasting impacts.

We are convinced to be a strong partner for the following reasons:

Choosing the right partner for data architecture topics is a critical choice as those decisions will have long-lasting impacts.

We are convinced to be a strong partner for the following reasons:

Choosing the right partner for data architecture topics is a critical choice as those

decisions will have long-lasting impacts.

We are convinced to be a strong partner for the following reasons:

Holistic vision

We consider the broader business context and strategic goals to design data architectures that drive tangible value.

Constantly seeking new paradigms & tech

We create both business and real-time embedded dashboards with frameworks like Tremor, enhancing data interactivity.

We split the noise from the concrete

We cut through the hype and complexity to deliver clear, practical, and actionable data architecture solutions.

From Architecture to Implementation

We bridge the gap between theoretical designs and real-world implementation, ensuring your data architecture is successfully deployed and operationalized.