Drivers for Managing Unstructured Data

So, what is structured vs. unstructured data?

Structured data is data with a defined data type and typically stored in a relational database making it easy to search.  Unstructured data is essentially “everything else” and includes things such as Emails, text files (such as presentations, spreadsheets etc.), social media, mobile data. In addition, there is machine-generated data that includes satellite imagery, surveillance, and sensor data. 

Why is it important to drive optimisation of unstructured data?

When creating or evolving an enterprise data management strategy it is crucial that this includes a plan to optimise the unstructured data element, especially when it comes to documentation.  With unstructured data growing by 55-65 percent each year, the scale of what organisations are dealing with seems daunting. 

The good news is that unlike the past, we now have the technology available to optimise this management of unstructured data to allow businesses to gain valuable nuggets of insights hidden in this data as well as drive efficiency throughout the business.  Another reason that this can’t be ignored, is that the pure amount of data (and it is growing significantly), adds business risk (including keeping data beyond retention periods is not advisable) and increasing costs (storage is not free). 

What are the drivers for optimising your unstructured data?

The drivers for optimal unstructured data management is in line with what one would expect when creating any data management strategy. You might be asked what are you set to gain from investing time and effort into addressing this?  The key benefits lie within visibility, accountability and simplicity.  

1 – Visibility 

For a business to drive efficiency and gain value from information captured in an unstructured way is to be able to know where things are and what the status is, of such information. To allow for this to happen, your strategy should include systematic ways of linking ALL data points.   

2 – Accountability  

With data protection regulations such as GDPR being front of mind, it is important that as part of the drive to optimise our processing of documents, that accountability and traceability should be achieved. Knowing and being able to easily track who did what and when, can be gained when you have an automated way of handling all types of documents and the management of unstructured data.    

3 – Simplicity 

As unstructured data is typically created with a different motivation to say entering a piece of data into a database, the creator is also less interested in making the relevant connections. For example when an email is received with an attachment, typically the end user will act on the request posed by the email, but not necessarily be thinking of attaching the document to the relevant customer record for example. The key is that it needs to be simple and ideally require no human intervention. In a world of AI and machine learning there are many ways of creating automatic links between structured and unstructured data as part of optimising your document processing.