Big Data is a key ingredient of the agri-food technology landscape.
The analysis of the agri-food supply chain is key in improving efficiency and reducing costs. Big data has become a critical element in this process.
From farm to fork, massive data sets of information are gathered at every stage of the supply chain, from environmental conditions that crops are grown under, applied agronomy, telemetry on farm machinery during harvest, through processing stages and ultimately storage and delivery. This data can provide invaluable insights into how farmers can improve yields, processors can increase efficiency, and supermarkets can reduce costs.
Data Language have the experience you need in big data analytics, and the design and implementation of semantically aware big data lakes and platforms.
Next generation big data
Unique expertise in implementation of semantic data lakes
Evidence based systems and analytics for decision support
Domain driven design for big data modelling
Domain modelling at Syngenta and Agrimetrics provided a guiding light through their big data ocean
Semantic models for evidence based analytics enable the meaningful comparison of questions framed on your data as input into decision support systems..
Data science is becoming an increasingly important tool in the Agri-Food industry. We are experts at building big data science platforms that deliver business value and are maintainable.
How do you make sense of a wealth of data in your supply chain?
A typical supply chain can generate a vast amount of data, in different forms, and distributed across diffferent systems. The potential for exploiting this data to identify inefficiencies is huge, but immensely challenging.
As in all our solutions, understanding the business need comes first. What are the questions you need your data to answer? Early domain modelling will help you understand the nature of your problem, and provide a roadmap to unlocking the value in your data.
By applying a thin layer of semantics on top of your big data solution, we will enable smart data lakes which are connected, meaningful, and governable. A logical polystore design pattern applies the right data technology for the types of data you need to ask questions of, allowing you to leverage the business advantage of a distributed, dynamic, and scalable source of knowledge.
Technically extremely good, right the way through from design and building to data infrastructure to software development of semantic web technologies. The guys are really personable which is really good.
If you would like to know more about Data Language or have a project you would like to discuss with us, then please get in touch.