Cloud Data Lake
and Data Lab design


Data Lakehouse Architecture

Our architects analyse and qualify the Use Cases, identify the data sources, define the data ingestion strategy & acquisition, plan & design data storage and data processing pipelines, establish an information security strategy and choose different forms of data consumption outputs.

Great Reading: Data Teams
Data Lake devops,
deployment and integration


Data Lakehouse DevOps

Increase the ability to deliver applications and services at high velocity by merging development and operations in one team. Our devops engineers work across the entire application lifecycle, from development and test to deployment to operations and have a range of skills not limited to a single function.

Build secure data lakehouses fast
Data Engineering and Data Ops


Data Engineering 

Our Data Engineers choose the right technologies to build scalable Data Pipelines and generate Data Products. DataOps works with the Analytics team to consume the Data Product in order to derive insights that drives business decisions.


10 Proven Steps to become a Data Engineer
streaming-data solutions


Streaming data solutions

Data streams can be processed on a record-by-record basis or over sliding time windows, and used for a wide variety of analytics. Information derived from such analysis gives companies visibility into many aspects of their business, (near) real time, making the organizational decision making processes multi-fold faster. Our engineers have deep expertise with designing, building and operating stream processing solutions.

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Data-driven applications

Our developers help you with the vision, definition, design, roadmap and development of your new End to End Data Driven Applications. We deeply understand and work with a variety of industry leading tools across the software development lifecycle spectrum.



Example Application


From Architecture design through DevOps to Data Engineering,
we work with the following partners.

Data and analytics have become a competitive differentiator and a primary source of value generation for organizations. However, transforming data into a valuable corporate asset is a complex topic that can easily entail the use of dozens of technologies, tools, and environments. AWS provides the broadest and deepest set of managed services for data lakes and analytics, along with the largest partner community to help you build virtually any data and analytics application in the Cloud. 



Azure analytics services enable you to use the full breadth of your data assets to help build transformative and secure analytical solutions at enterprise scale. Fully managed services like Azure Data Lake Storage Gen2, Data Factory and Databricks, help you easily deploy solutions for BI and reporting, advanced analytics, and real-time analytics.


Founded by the original developers of Apache Kafka, Confluent delivers the most complete distribution of Kafka with Confluent Platform. Confluent Platform improves Kafka with additional community and commercial features designed to enhance the streaming experience of both operators and developers in production, at massive scale.


At Cloudera, we believe that data can make what is impossible today, possible tomorrow. We empower people to transform complex data into clear and actionable insights. Cloudera delivers an enterprise data cloud for any data, anywhere, from the Edge to AI. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises. 

Technologies and tools we love

The top notch technologies we use, accompanied by a broad range of technical expertise set us apart from other consultancies.


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