Transform Big Data into business value

We apply state-of-the-art technologies to your data, extracting meaning that you can use to create new value for your organisation

DataStork takes huge datasets and makes them useful. We do this using technologies that derive semantic meaning from diverse databases and vast quantities of unstructured data. You get to use data that is already in your organisation in new productive ways, gaining efficiencies and creating new competitive advantages.

Transform your data into knowledge

Solutions design and architecture

DataStork can help you accelerate your organisation‘s Big Data revolution. Our experience helping organisations of all sizes means we bring proven strategies which have been successfully deployed across multiple sectors. We brief you on up-to-the-minute advances in Big Data technologies, assist you in designing high-value, high-return solutions and help you minimise risk and optimise the ROI of your technology investment.

Semantic data modelling and ETL

DataStork excels at building effective ETL (extract, transfer, load) pipelines which are the backbone of Big Data transformation operations. We create continuous ingestion, data modelling and reconciliation solutions that bring together diverse data from sources inside and outside your organisation. Mapping the data to a customised domain model creates opportunities to conduct analysis across the combined data set, automating and accelerating processes and making possible analysis that could not have been achieved before.

Text mining and analytics

Businesses everywhere face the challenge of exponentially-growing unstructured and structured data. We can help by building a new custom data pipeline or optimise an existing pipeline to deliver higher-quality text analytics, whatever your business objectives. We use industry-leading tools from vendors such as Ontotext to contextualise text data, transforming it from raw data to a meaningful, searchable asset.

DataStork in action

Building AI-driven semantic classification for the Financial Times

The Financial Times – the world’s leading financial – publisher needed a way to integrate AI-driven semantic document classification to its high volume newsfeed. DataStork helped develop the product over 18 months, delivering a cutting edge technology stack:. 

The engineering infrastructure was built with Jenkins and Docker, and deployed in the Cloud. The solution is now in production processing hundreds of thousands of documents with millions of annotations on a daily basis in a number of big financial and pharmacy companies.

Technologies used: Java/Spring, PostgreSQL, MongoDB, ElasticSearch, REST API for the backend and an Angular2 web app for the front-end