Big Data Defined
The easiest answer: Big Data is your data, structured and unstructured.
There’s nothing new about the notion of big data, which has been around since at least 2001. It’s the information owned by your company, obtained and processed through new techniques to produce value in the best way possible. Big data may be as important to business – and society – as the Internet has become. Why? More data may lead to more accurate analyses.
Ask any Big Data expert to define the subject and they’ll quite likely start talking about “The three V‘s”. As far back as 2001, industry analyst Doug Laney (currently with Gartner) articulated the now mainstream definition of big data as below:
- Volume. Many factors contribute to the increase in data volume. Transaction-based data stored through the years. Unstructured data streaming in from social media. Increasing amounts of sensor and machine-to-machine data being collected. In the past, excessive data volume was a storage issue. But with decreasing storage costs, other issues emerge, including how to determine relevance within large data volumes and how to use analytics to create value from relevant data.
- Velocity. Data is streaming in at unprecedented speed and must be dealt with in a timely manner. RFID tags, sensors and smart metering are driving the need to deal with torrents of data in near-real time. Reacting quickly enough to deal with data velocity is a challenge for most organizations.
- Variety. Data today comes in all types of formats. Structured, numeric data in traditional databases. Information created from line-of-business applications. Unstructured text documents, email, video, audio, stock ticker data and financial transactions. Managing, merging and governing different varieties of data is something many organizations still grapple with.