How to manage big data in the age of digital

In today’s digital world, businesses are increasingly focused on a digital-first approach or implementing new initiatives to encourage digital transformation.

As a result, both organisations and individuals are forced to get to grips with certain changes. While consumers might be faced with adapting to a new app or a different way of consuming content across a variety of devices, organisations may have to review an entire business.

Analysing business systems and processes which have fulfilled objectives thus far is the first step towards re-imagining operations and focusing on the way in which digitisation could trigger enhanced productivity or improved services.

In the age of digital, many organisations find it difficult to cope with the increasing volume of information and data flowing across the business. It’s easy to leap to the conclusion that more data equals more value for companies, but this is far from the truth.

>See also: How to take the long term view on big data in healthcare

While big data can be a huge asset, it can also become a real burden when an organisation lacks the management and internal processes required to handle it successfully.

In these cases, it quickly overwhelms the business while offering limited value. Yet, once the right processes and infrastructure are implemented to manage the increasing growth in high-volume data, big data can become an organisation’s most valuable asset.

Across every vertical, organisations of every size are searching for methods to efficiently extract maximum value from both structured and unstructured big data in order to apply it to business decisions and drive organisational success.

Yet a recent study from Capgemini revealed the extent of this struggle, demonstrating that less than a third of big data projects are actually profitable.

Even in today’s digital age, limitations in traditional business intelligence (BI) tools make extracting value from big data a difficult task.

This is further compounded by a lack of data analytics resources in many organisations. Faced with these challenges, how can businesses evolve processes to turn big data from just visible to truly valuable?

In order to answer this question, businesses must consider the stages of handling high-volume, unstructured data growth:


The sheer volume of information available today continues to grow exponentially.

Organisations are moving away from the days of siloed information where data was neatly stored in separate systems of record and an increasing amount of data is now collected by every single team, department and employee within a business.

As a result, the full life-cycle of information – from creation, to governance and compliance to archival and finally disposal – must be carefully managed across a company in order to keep it under control.

>See also: Using big data analytics to win back customer confidence

Whether the data is stored on an ERP or CRM system, on email, on individual devices, on-premises or in the cloud, businesses must break through silos to build a comprehensive picture of data across the organisation in order to ensure success in today’s digital world.

Report and visualise

After an organisation has gained complete visibility into where information is kept and understands the scale of data and information being created, steps can be taken to develop processes which allow IT to understand what information is available to the business.

Simple, graphical dashboards are increasingly being used to report on available data. These might focus on what proportion of data is stored in the cloud as opposed to on-premises or to what extent data is available in emails instead of on a secure ECM or CRM system.

Once business data can be visualised across every department to create one whole image, patterns will begin to emerge and any issues or bottle-necks will come to light. With this visualisation in place, the map of unstructured content that makes up so much of the data stored in and used by a business starts to take shape.


It just isn’t possible for a human to read, process or understand all of the information that is available today.

However, with advances in technology, machines can now differentiate between an invoice and a contract, or a social post and a letter, or an article in a newspaper and an instruction manual.

As a result, organisations can make real, data-driven decision based on a combination of machine speed classification and both sentiment and big data analytics.

With analytics tools, businesses are able to understand exactly how the organisation is performing today – as well as starting to predict how it will operate in future.

>See also: 10 predictions for the Internet of Things and big data in 2017

In this way, organisations are able to make the most of current technology to predict how a company’s behaviour will impact future plans and calculate business success.

By building a single platform for both unstructured and structured data, companies can put big data to work and tap into a range of benefits.

Creating one comprehensive picture of business data while employing smart analytics and reliable forecasting enables organisations to save time, reduce costs and make authoritative business decisions based on real data trends.

The data is there – readily available for organisations to utilise. However, businesses have to make the decision to put processes in place which can transform idle information into actions that drive organisational success. This is the first step to deriving true value from big data.


Sourced by Muhi Majzoub, EVP Engineering at OpenText

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Nick Ismail

Nick Ismail is a former editor for Information Age (from 2018 to 2022) before moving on to become Global Head of Brand Journalism at HCLTech. He has a particular interest in smart technologies, AI and...