February 2018 saw the eagerly anticipated release of Nalytics v1.10. This release has a strong focus on what we term data enhancement. What do I mean by data enhancement, I hear you ask? Well, this is a series of capabilities within the Nalytics product that will surface key information, making it easier and quicker to discover insights and find what you are looking for. Read on to find out more…


For some time we have provided enhancers that will look through data sets and surface terms that an organisation is particularly interested in. We store the terms of interest in dictionaries. An organisation may have dictionaries containing things such as their employees, clients, project names, product names, or perhaps domain-specific terminology (such as legal terms or social care alerts). Enhancing with these dictionaries creates category lists containing the values that have been found in the data. Users can then find all instances of selected values in their data at the click of a button. More than this, Nalytics provides various ways to visualise category values to find out things such as, the relationship between category values; which of our Lawyers has had dealings with this client, for example. Anyway, in V1.10 we make our cool and extremely useful enhancers even easier to use by providing an intuitive dictionary maintenance interface. Authorised users now can create and maintain dictionaries from inside the Nalytics client. As well as this, users can now select the dictionaries they want to use when enhancing any given data set so they only use the dictionaries relevant to the data they are interested in surfacing.


We have added a new enhancer to the mix as well. Our date enhancer roots out all dates in a data set. It doesn’t mind what format the date is in – we support all commonly used formats including American. So, the date enhancer surfaces dates and makes locating them in your data a piece of cake. More than this though, it will try to identify what type of date it is, using terminology you can configure. For example, you may want to see contract end dates, renewal dates, dates of birth and so on. Now you will be able to do things like, find all contracts that will expire in the coming month. All this in unstructured data with no reliance on prior knowledge of document composition or pre-building of models. Really powerful, I think you’ll agree.


Last release saw us introducing a means of surfacing personally identifying data (PID). This innovative capability will seek out any data pattern you are interested in; think bank account numbers, email address, NI numbers, postcodes, telephone numbers, the list goes on. From a GDPR perspective, this is invaluable. Nalytics automatically finds and surfaces personal data and enables you to locate, not only the documents or other data sources containing the personal data, but also shows you exactly where in the documents/data sources the data occurs. In this release, we have added a counter that indicates the density of personal data, i.e. how many types of personal data any given document contains. This can help with prioritisation when looking to assess GDPR compliance.


OK, that’s it for v1.10. Talk to you soon about the exciting capabilities in our next release.