There has been a lot of hype surrounding Big Data and how the information explosion, and resulting complexity, is now a top priority for businesses – some vendors have even suggested that organisations face yet another a ‘rip and replace’ watershed. However, analysts have commented that any new technology should be complementary to existing tools, not an alternative. While there has been much discussion about what companies can hope to achieve with Big Data once they’ve overhauled their entire existing infrastructure, businesses should instead be focusing on how they can use this information today.

According to IDC, Big Data is ramping up to be a big business opportunity, with companies on average doubling the amount of data they create every two years. The firm also estimates that companies will spend $120bn globally on data analytics software between now and 2015. Due to this exponential growth in information, managing and organising data is becoming increasingly complex for businesses. Traditional relational databases are becoming less useful and relevant as more ad hoc information is being created outside of those systems. But, while Business Intelligence (BI) tools have been around for a while to extract value from relational databases, few companies currently have the technology in place to apply the same degree of sophistication to unstructured data, such as call transcripts, documents, emails, instant messages and social media. What is different about Big Data is that it includes sources that were previously ignored; unstructured data being the main one, which itself contains a myriad of untapped and valuable information. Data left unmanaged and un-analysed is worthless. In fact, it can be problematic as it represents a cost to the business in terms of storage and may leave a company vulnerable to compliance concerns. The ability to extract meaning from data is where its true value lies.

Informed business decisions must be based on the totality of information and not merely a subset of transactional data from a relational database. Unstructured data by its very nature is uncategorised and lacks the metadata that allows for easy identification and organisation. This can potentially leave data in a state of chaos, exposing the business to legal and compliance risks – especially those in regulated industries. This can end up costing businesses vast sums of money to analyse information on a purely reactive basis. As such, organising, managing, and analysing this chaotic data proactively is a more cost effective approach, and can provide businesses with valuable insight through the evaluation of unstructured data. If businesses rely on structured information alone, they are potentially missing out on key information spread across its disparate systems within the organisation as well as conversations taking place between its customers, and the business beyond its four walls.

The real ‘big’ in Big Data is the amount of unstructured data that businesses now have to manage and track. Businesses should be able to build up a customer profile to analyse and calculate risk through the collection of data from various mediums. They need solutions - whether they are internal or outsourced - that can help employees effectively access key information through predictive information management and analysis. The only way to do that at the scale of big data is to use machine learning to automatically categorise and analyse that information. . Without these solutions, businesses may be exposed to legal and compliance issues run the risk of not being able to respond to their customers, respond to their regulators or react quickly to threats of litigation.. This again highlights the importance of getting to grips with unstructured data as well as structured data, but how can businesses organise this chaotic landscape?

Integral to this is the ability to identify, understand and categorise the key information amongst the vast amounts of unorganised and unstructured data. Traditionally, it is held on file servers, in document management systems, archives records management systems. But extracting value from the information held there is usually very hard because it wasn’t stored in any uniform way and wasn’t categorized accurately.

But now software exists that can accurately index and categorise such data that resides in these repositories and can extract intelligence that aligns with business goals, this providing a competitive edge and reducing legal and compliance risks. Businesses must know what information resides within their systems; be it structured, semi-structured or unstructured data. By using software to identify words, phrases and concepts in context businesses can embrace and take advantage of the data explosion, rather than living in fear of it overwhelming them.