Consono’s Strategic Data Canvas is a five-step method to making strategic use of your data.
The five steps include the need to identify your data, then link it, explore it to understand it, enhance it so you can apply it, before finally exploiting it in a strategic way.
Step one is having a clear understanding of what your data contains, where it is and who has access to it. The Dynizer uses AI and NLP for document type identification, abstract entity and role detection, and context-specific text summarization to help classify documents and their narrative data content to make them compatible with relational data.
Having an up-to-date overview of your data is essential to step two – linking the data to make it usable. All your data should be accessible in near-real time for people to use and to analyze.
The Dynizer links and indexes data, controls quality and management, then clearly defines and monitors data exchangeability.
Step three distinguishes the Dynizer from any other solution – the ability to see the links between multi-structured data without usage-specific transformations.
The Dynizer understands cross-model links between data to access almost any part of the data from many viewpoints, no matter what its technical characteristics. Data modelling is automatic, and querying is data-less.
Step four is about enhancing the data to better apply it to what you do – and that also means being aware of what you don’t know and having a strategy to fill in the gaps.
You need to be able to monitor data in real time and use that information to forensically examine the ‘who knew what, when’ of data usage. It’s important, too, to have a more global view of your data and to restrict access for people, groups, and roles to satisfy GDPR regulation through pseudonymization. Data can be reused without duplication.
Everything comes together in step five. The Dynizer’s agnostic analytics allow you to use data strategically to improve your business. The Dynizer has tone of voice detection built in. Data-less querying means being able to search the data you don’t know, quickly and simply. Summarize results without bias or clutter.
Investigate operational options through real time access to the relevant data and use AI to prepare data in a better way.
Gather complementary data from other sources to increase your insight.
Finally, you need the accurate metrics that will measure how your data best fits with your field of interest.
