By even the most conservative estimates, the amount of data in the world doubles every two years. Most data is flowing into the enterprise at alarming rates, ranging from data-in-motion to dark data (or the operational data that is not being used). IDC estimates that ninety per cent of digital data is dark, which means companies are missing a major opportunity to boost the bottom line – they just need to turn on the light.
Gartner defines dark data as 'the information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes.' As enterprises continue to collect data on an epic scale, it is occupying precious storage space, and is costly to revisit and analyse.
By implementing a fast data solution in a data pipeline, organisations can derive value from data in real-time before it goes dark. Essentially, one can minimise the storage of dark data while maximising the business value of real-time enterprise information. This approach to dark data has many benefits:
Avoid lost value of epic amounts of enterprise data
Many enterprises are sitting on treasure troves of data that is stored away and rarely accessed, causing it to go dark. Dark data’s significant business value is thus limited. Dark data also consumes significant storage. By applying a fast data approach to data in the pipeline, and putting dark data to work, enterprises can extract real-time information allowing actions and decisions to be made based on real-time information. By doing so, enterprises can make the most of every data point that comes their way.
Avoid difficult and costly analysis of unstructured or semi-structured data
Many enterprises struggle with the epic amounts of company data they collect. Too much of that data is stored and rarely accessed or analysed. Once unstructured or semi-structured data is entered into a Big Data store, it can be a long and expensive process to extract its value without extensive analysis. It is much more efficient, in terms of time, money, and resources, to derive value from data in real-time.
Immediately analyse and act on real-time information
When data is stored, it loses real-time value - and with that comes missed opportunity. It can be months before the data is available again to analyze and act upon. Implementing a fast data solution in a data pipeline allows organisations to immediately analyse incoming data and act on that real-time information. A batch approach to storing and analysing data leaves you steps behind today’s fast paced, real-time industries.
Gain insight into sales, production, and distribution trends
When data goes dark, enterprises generally fail to use it other than as a historical informational asset - its immediate value is lost. By extracting value from data before it goes dark in real-time, businesses can gain invaluable insight into production, sales, and distribution trends, and can thus make more educated, beneficial and timely decisions for their company.
Minimise the accumulation of dark data to maximise the value of real-time information
Extract value from data before it is dark to avoid the storage problem that comes warehousing with dark data while maximising the value of real-time information.
Peter Vescuso, Chief Marketing Officer at VoltDB