Data Engineering

Data Engineering

JRAH have the experience required to implement a modern data management and analytics platform for your organisation, whether it be in an on-premise data centre or in the cloud.

Data Storage

Not all data is created equal. When designing your data management or data analytics platform you need to decide how to store your structured, semi-structured and unstructured data.

There are a vast number of excellent technologies to choose from. Picking the right one based on your functional and non-functional requirements can be challenging. We have worked many of the market leading data storage technologies including relational databases, NoSQL databases, time series databases, data lakes and BLOB stores and can help you to make the correct choices.

Data Pipeline Automation

Whenever possible, we implement metadata and template driven data ingestion and data quality pipelines or workflows. This gives significant productivity and quality benefits and enables use to deliver high quality solutions more quickly and at a lower cost than many of our competitors.

Data Lake Design

There are many technology solutions available for implementing a Data Lake. However, there are some basic concepts that should be considered when designing a useful Data Lake:

Tagging and cataloguing: All data ingested into the lake should be tagged and catalogued so that users can search for and find the data that they need

Security: The data in the lake should be secure, both in terms of who is allowed to access it and how it can be recovered if things go wrong

Costs: The volume of data and the method of storage will have a significant impact on the cost of running your Data Lake. Your budget and non-functional requirements need to be considered during the design of the lake.