Big data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analysed for insights that lead to better decisions and strategic business moves.
Why Is Big Data Important?
The importance of big data doesn’t revolve around how much data you have, but what you do with it. You can take data from any source and analyse it to find answers that enable 1) cost reductions, 2) time reductions, 3) new product development and optimized offerings, and 4) smart decision making. When you combine big data with high-powered analytics, you can accomplish business-related tasks such as:
- Determining root causes of failures, issues and defects in near-real time
- Generating coupons at the point of sale based on the customer’s buying habits
- Recalculating entire risk portfolios in minutes
- Detecting fraudulent behaviour before it affects your organization
What’s big data’s potential?
The amount of data that’s being created and stored on a global level is almost inconceivable, and it just keeps growing. That means there’s even more potential to glean key insights from business information – yet only a small percentage of data is actually analysed. What does that mean for businesses? How can they make better use of the raw information that flows into their organizations every day?
The Three ‘Vs’ of Big Data
The amount of data matters. With big data, you’ll have to process high volumes of low-density, unstructured data. This can be data of unknown value, such as Twitter data feeds, clickstreams on a webpage or a mobile app, or sensor-enabled equipment. For some organisations, this might be tens of terabytes of data. For others, it may be hundreds of petabytes.
Velocity is the fast rate at which data is received and (perhaps) acted on. Normally, the highest velocity of data streams directly into memory versus being written to disk. Some internet-enabled smart products operate in real time or near real time and will require real-time evaluation and action.
Variety refers to the many types of data that are available. Traditional data types were structured and fit neatly in a relational database. With the rise of big data, data comes in new unstructured data types. Unstructured and semi structured data types, such as text, audio, and video require additional pre-processing to derive meaning and support metadata.
The volume, velocity and variety are key to the success and growth of big data in the future. Many businesses and industries are going to see the increase of big data as part and parcel of how they operate, so why not get a head start?