Turn data that is too large, fast or complex for traditional tools into insight your business can act on.
Big data is a term for data sets that are so large or complex that traditional data processing software is inadequate to deal with them. Challenges include capture, storage, analysis, curation, search, sharing, transfer, visualisation, querying, updating and information privacy.
The associated solutions cover a wide range of technologies and techniques that let you extract real, useful and previously hidden information from very large quantities of data that would otherwise have been left dormant because storage was too costly.
In essence, big data is data that is valuable but, traditionally, was not practical to store or analyse because of the cost or the absence of suitable mechanisms.
Most big data discussions are framed around a handful of characteristics. Together they describe why traditional tools struggle and what a modern platform must handle.
Big data solutions store and process hundreds of terabytes of data, and the total volume is growing many times over every few years. Storage must be easily expandable and work efficiently across distributed systems, scaling out across many machines.
New data often does not match any existing schema. It can be semi-structured or unstructured, such as text, audio and video, so applying a rigid schema before or during storage is no longer practical. It needs additional processing to derive meaning and supporting metadata.
Data now arrives at an increasing rate from a fast-growing number of devices, users and applications. Streams from web pages, mobile apps, network traffic and sensors must be handled efficiently and turned into results within an acceptable timeframe.
Large, fast and varied data is only useful if it can be trusted. Quality, lineage, auditability and privacy have to be managed across every source so that the conclusions drawn from the data are dependable.
Data has intrinsic value, but it has to be discovered. Quantitative and investigative techniques can reveal a consumer preference, drive a relevant offer or flag equipment that is about to fail. The real challenge is human: asking the right questions and recognising patterns.
Whatever big data challenges your organisation faces, we can provide you with the strategic guidance you need to succeed.
