Unstructured Data – the Unsung hero

Unstructured Data – the Unsung hero

Unstructured Data - The Unsung Hero

“To be able to bring out the potential in the unstructured data and put it to use can make the difference in validating customer-centric strategies and the digital transformation journey.” - Technology and digital transformation expert from a leading financial services company shares the importance of unstructured data and the need to secure it.

In their journey towards digitalization, organizations are increasingly focusing on customer centricity and reinventing the business models to gain an edge over competition. Data plays a vital role in this journey.

Organizations generate huge volumes of data, especially from the customer-facing applications from across content and social media formats. Any kind of data that cannot be compiled in a recognizable or predefined structure is termed as unstructured data.

It is important that organizations find ways to manage and analyze this data that can boost business growth and revenue streams.

What is the role of unstructured data in the digital transformation? How can organizations leverage on this data to generate actionable insights in the highly competitive ecosystem?

Data lies at the heart of digital transformation and powers business insights from data analytics. Amount of data generated daily is mind boggling and 90% of it is unstructured data. To fully realize the potential of unstructured data, organizations need to move out of data silos and choose scalable data hubs. By having the systems to store, analyze and report data from a variety of sources including humans and machines, organizations can finally unleash the enormous value of unstructured data.

Sources of these data are vital to any organization, and include emails, photos, videos files, documents, web pages, blog posts, social media, presentations, transcripts, survey responses, chat interactions, voice, emails, IoT etc. Additional sources of such type of data in BFSI organizations are data from CRM systems, financial filings, KYC forms and text messages.

Unstructured data cannot be stored without transformation and usually it’s an overkill to change the unstructured data into a structured form. It makes sense to put the energies to infer the data and focus on the desired outcome using AI and ML tools. These AI and ML powered tools can enable organizations to leverage analytics to access insights in the unstructured data. Few real -world use cases are scanning of invoice data, email classification, fraud detection etc.

Tapping into information requires solid data routing mechanisms and AI based algorithms that can periodically clean this data. We have the Natural language processing tools that make it possible to translate sentiments, recognize patterns, enable speech-to-text conversion through machine learning. This information then becomes a strong tool to establish customer profiles, analyse businesses processes and validate your business strategies.

Social media is another potential source of unstructured data that practically speaks for the customers and can provide insights into habits, preferences, gaps, expectations and behaviour of customers. Combine this with the analytics from structured data and organisation can uncover comprehensive insights to design strategies, enable customer centricity and enhance services.

Data security is a major concern while dealing with unstructured data? What ae the risks and how can organisations deal with the risks?

Unstructured data does not adhere to any standards and it lies outside the data organizing framework. This data can become a nemesis of a potential data breach or a ransomware attack.

An intelligent data-management system can achieve the task of categorizing the data and extracting relevant data sets. Especially for companies in the BFSI segment, the unstructured data hold huge potential and hence it is inevitable that organizations deploy optimum security along with a robust data recovery system. Data breaches and abuse of highly confidential or sensitive information is a threat and there has a been a rise in cases of ransomware extortion by encrypting the critical data.

A chain is only as strong as its weakest link; and this applies to data security too. Not being able to secure and protect unstructured data can become a huge hindrance in accelerating the digital transformation for an organization. In such cases, the organization needs to address two aspects of managing unstructured data. First is the storage and second is the recovery in case of an unfortunate cyber-attack.

Storage is key because storing huge volumes of unstructured data is a costly affair. NAS or cloud-based file sharing technologies have come across as a faster and stronger mechanism to store and secure the data with built-in security layers.

When it comes to security knowing the data is the first step to prioritize information into critical and non-critical to assign security controls. A Zero Trust security architecture with continuous security analytics can identify potential threat in advance. However, to protect the data, immutability is vital. Embedded levels of security along with a robust system for recovery and compliance can enable data immutability. Especially in the case of banks and financial institutions that are heavily regulated by compliance, an immutable data recovery system assures protection against ransomware attacks and minimum downtime. The cost of data breach can be drastic. An automated recovery model supported by access control and minimized data exposure can mitigate the disruption.

The BFSI sector generates volumes of unstructured data and it plays a vital role in the digital transformation journey and creating a data-driven future for the organization.  Unstructured data cannot be left unutilized and unsecured.