Big Data Vs Big Content

Big Data Vs Big Content

Big data is a topic that is impossible to ignore, but already a new and potentially much more compelling challenge is emerging: Big Content. As organisations are faced with ever-growing volumes of raw information, many have attempted to work out an effective way to convert this data into useful consumer information.

Through the advancement of business intelligence, real-time reporting, and transactional data insights, many are only now beginning to truly utilise the information made available to them. At the same time, many remain plagued with questions as to how they can manage and visualise the insights that they have gained from Big Data.

When considering Enterprise Content Management (ECM) and Information Management, we are often required to address the problems raised by both structured and unstructured content. Traditionally, when organising a company’s information, a mere 30-40% will exist as the structured data that has formed the foundation of Big Data.

But beneath this surface, there exists a wealth of unstructured content in the form of documents, emails, videos and images that many organisations are incapable of organising effectively, and therefore unable to use this wealth of information to the benefit of the business. It’s the mobilisation of this information that is becoming known as ‘Big Content.’

Traditionally, data consists of quantitative information that can easily be collected or logged within a table. Content on the other hand, is considerably less tangible. Examples of unstructured content could include email attachments, document comments, and written customer complaints. This information provides an equally vital source of business intelligence, yet one that, due to its unstructured nature, is often overlooked.

As with the recent explosion of Big Data, the digital age has been a driving force in the rapid expansion of unstructured content. As more business practices shift online, organisations collecting vast quantities of customer information and user generated content.

This trend has accelerated within social networking sites, where customers regularly leave comments and feedback. While there are many online services that attempt to structure this information and convert it from qualitative content to quantitative data, these tools often fail to capture the full extent of the information’s meaning.

This is particularly true of aspects such as sentiment, which is notoriously difficult to quantify. Similarly, much of the content that is uploaded to social networking sites takes the form of image files and video footage. Such unstructured formats will often be ignored by organisations’ information strategies, usually because they do not conform to the traditional methods of data collection, namely databases and spreadsheets.

It is this unseen information that we as business professionals need to understand. By drilling down beneath Big Data, organisations can attempt to get to know their customers on a more human level. We must look beyond the hits, page views and bounce rates that make up Big Data, and focus instead on the intelligence held within unstructured content. Only then are we able to provide some form of context to the raw data we are attempting to collect.

If organisations wish to truly inform their business decisions, they need to start mining not only their customers’ data but also their customers’ content and the content developed from within their own organisation. By undertaking this task now, they will be better prepared to face the future challenges that will inevitably surround Big Content.

Despite this similar approach, Big Content should not be treated as a replacement to Big Data, it is simply an additional factor that organisations must address when planning their infrastructure and information management strategies. By undertaking a ‘ground-up’ approach and encompassing information management into all stages of an organisation’s strategy, businesses can reduce the need for costly hardware updates to deal with Big Content.

Rather than attempting to overhaul their current systems by installing larger storage solutions and faster processors, many organisations simply need to optimise their existing approach to information management. By ensuring that both Big Content and Big Data are collected and addressed throughout each and every business process, organisations will be better prepared to save time and cut costs in future. Only once these initial practices are in place should advancements in hardware be installed.

Currently there is a risk that businesses are too focussed on Big Data and information they can fit into existing data capture tables. Addressing Big Data and Big Content in tandem can give businesses a significant commercial advantage and help them to truly understand customer behaviour. The challenge is finding an approach that can understand and capture both types of information.

Organisations must begin to develop clear roadmaps for managing their information in future. This process should involve a strategic approach to Enterprise Search and semantics, ensuring that the right information is available to both customers and employees. Such an approach should not be considered a technical update, but rather a complete shift in the organisations corporate culture. Only then will they be truly prepared to face both Big Data and Big Content.

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Vikram Setia

Vikram Setia is the co-founder and Commercial Director of infoMENTUM, the UK’s only dedicated UK Information Management consultancy holding both Oracle Enterprise Content Management and WebCenter specialisations. Prior to founding infoMENTUM Vikram spent over 15 years experience working as an Information Management consultant for a range of large organisations. Specialising in information management, enterprise search and Ontologies and Semantic Web, Vikram is an expert in information communication technology working across a range of verticals markets.