In this blog post, Northdoor explains how automated data discovery and classification can help organisations not only respond more efficiently to regulatory requests but also make better use of their data. In the typical organisation today, the sheer number and variety of systems can make it difficult to find valuable data, such that opportunities for profit may be missed. By introducing automated data discovery and classification, organisations can more easily and rapidly transform raw data into business insight and competitive
In the vast majority of cases, organisations are somewhat disorganised when it comes to managing data. It’s all very well having strict data governance policies and finely tuned hierarchies in your core ERP or financial solutions, but what about the accompanying long tail of applications, messaging systems, data stores and archives? Flexible cloud storage and software-as-a-service offerings have made it all too easy for business users to bypass what they see as overly restrictive IT policies. The resulting “shadow IT” infrastructure may contain as much data as the real infrastructure, but spread across hundreds or thousands of locations, in diverse formats, structured and unstructured.
On the one hand, the proliferation of unmanaged and ungoverned data represents a risk in terms of compliance with regulations such as the GDPR (for more information, see our blog post on SARs). On the other hand, it represents a significant missed opportunity. Data is the lifeblood of the information economy, and organisations usually work better when everyone is using the same data. When important business data is spread across large numbers of internal and external systems, and managed by individuals or small teams, vital insight may be unavailable to the majority of people in the organisation. Worse still, even within those silos of information, unstructured data may be sitting idle, its value completely invisible to the people who stored it there.
We all know how frustrating it can be when we can’t find that crucial email or document. Whether it causes a missed sales opportunity, a delayed response to a valued customer, or an embarrassing internal delay, the inability to locate data is a major drain on corporate efficiency. On a larger scale, the lack of a consistent, organisation-wide system for classifying and understanding data impedes the ability to put that data to work. When data is isolated and siloed, it’s impossible to see the full picture or to get full value from innovative technologies like data mining and machine learning.
To unlock the hidden value of these treasure troves of data, enterprises need the ability to understand and classify all existing and incoming data – without necessarily requiring any disruptive reorganisation of existing systems.
After all, in many cases there are excellent operational reasons for managing data in different systems. What’s needed is a comprehensive set of policies to classify and govern data throughout its lifecycle, regardless of where it may be physically stored at any given time. Naturally, this is only workable if it’s backed by an extensive system of intelligent automation, enabling incoming data in any format to be understood in terms of its content and potential value to the business.
At Northdoor, we have specialised for decades in transforming raw data into valuable business insight. Working with a major industry partner, we offer a rapidly deployed solution for discovering and classifying data in practically any format. The solution provides easy-to-use, wizard-driven interfaces that give business users the power to set rules and policies for automatically understanding and tagging data in both structured and unstructured formats. It includes templates for common data types, and enables users to create their own dictionaries and keywords.
With all existing and incoming data automatically classified and monitored throughout its lifecycle, your organisation can use rules-based management to keep track of the data you hold at all times. Heuristics and sophisticated algorithms make it easy to identify and use data sets for purposes such as data mining and machine learning, ultimately helping you unlock the full value of your diverse data.