Providing insights from your data, enabling you to make more informed decisions.
Deriving value from data residing in external sources, can be costly, time-consuming and sometimes impossible to achieve due to integration, formatting or quality issues. The same can apply to data from internal systems.
Our data and analytics platform, Agility, has three major components:
Big Data Platform
Our big data platform is a scalable data refinery capable of ingesting and transforming large volumes of data from diverse sources, in a secure environment. It delivers good quality, clean data, providing actionable insights to our customers.
The underlying technology for this platform is Lexis Nexis Risk’s High Performance Computing Cluster (HPCC), a proven and enterprise-tested open source platform for manipulating, transforming, querying and warehousing big data. HPCC has been utilized over the past 15 years to process Petabytes of data for the Global Insurance Market, utilizing the same technology to process the large and diverse datasets traditionally associated with the agricultural industry.
The defining feature of HPCC is its ability to scale horizontally – i.e. if you need to handle more data quicker, you can add extra nodes to your Cluster – meaning that there’s no limit to the volume we can process.
Generic big data processing is becoming more commonplace, however this is not good enough for agriculture where domain understanding is crucial. We have embedded our extensive agricultural knowledge throughout our big data solution.
Data visualization platform
Our data visualization solution is:
Widgets based: the platform allows you to build your own “data stories” by selecting from and configuring a range of agricultural spcecific widgets. The view and content of each widget is configurable by the user.
User preference driven: widget configurations and dashboard layouts are stored as preferences against individual users, allowing each user to create their own estate of visualizations and analytics.
Access and entitlement at multiple levels: user access and entitlement can be configured at multiple levels – widget, functionality and data. This approach allows us to define hierarchical entitlement structures to cater for organizational requirements – i.e. Regional Managers capable of seeing dashboards/data for their own regions, whilst Store Managers are limited to their own.
Dedicated Data Science Capability
The multi-dimensional nature of the agricultural industry requires a higher degree of analytical capability that can only be provided by data scientists with a background in environmental sciences. Our team of data scientists develop and apply complex and domain-aware heuristics for the purposes of data hygiene and insights generation.