BIG Data... But What Is It?

Much like the accompanying graphic of this weeks post, big data is complex and can be a lot to take in and process, let alone analyse and make good sense of. However, that doesn’t mean it is not worth analysing! Big data can tell us so much about businesses, economies and markets, and is a crucial part to an organisation's operations and performance. Something that really stood out to me in this weeks class is the six V’s that categorises the kinds of information that big data can provide, and how these can manipulate and influence organisation’s business decisions in terms of marketing.

Big data is ‘datasets whose size is beyond the ability of typical datable software tools to capture, store, manage, and analyse’ (McKinsey, 2011). Data can be collected through sensor data, social media, and is available as audio, images, video and unstructured text. This data can be analysed to reveal trends, and associations, often more specifically related to human behaviours.

Big Data captures an abundance of information that marketers can take advantage of. The data that is collected is often characterised using the six V’s…

• Volume

• Variety

• Velocity

• Veracity

• Variability

• Value

Volume - the magnitude of the data. Big data is reported in multiple terabytes and petabytes. For perspective, 1 petabyte is equal to 1,000,000 gigabytes.

Variety - the structural heterogeneity in a dataset. Big data can be structured, semi-structured, and unstructured data. There is also variety in the forms of which this data is collected; internal sources (sensors) and external sources (social media).

Velocity - the rate at which data is generated and the speed at which it should be analysed and acted on. For example, 2,083,333 Snapchats are sent every minute and thats just Snapchat alone, not to mention all other social media applications and internet servers.

Veracity - is the unreliability of some sources of data. This kind of data can refer to customer sentiments, as there is a level of uncertainty due to individual judgement.

Variability (and complexity) - the variation in the data flow rates; Velocity is not always consistent, and with multiple sources of data, it makes it difficult to connect the dots so to speak, in that data needs to be linked, matched, and transformed from different sources.

Value - it is often seen that big data is of ‘low value density’, meaning that its value is quite low in comparison to its volume. It is only after we have ANALYSED that data that it becomes ‘high value’.

Even though big data can be hard to analyse due to its large volumes, once analysed, it can improve business operations and production, to create a more effective and efficient business. For example, my dad runs the IT department for a fruit and vegetable company called Nutrano. Nutrano uses big data they have collected to help predict how much of each fruit and vegetable they need to grow, how many crops they need, where to distribute most of their goods, and how to transport the fruit and vegetables in a way that is going to be the most cost effective and environment friendly. It is even used to help with predicting weather patterns, which they use often for seasonal fruits and vegetables, as well as for things that a lot of us probably wouldn't think about; like knowing which direction the wind is blowing for when they need to spray crops etc.

So you can understand why Big Data is so crucial to businesses and marketing. It is a way for businesses to understand their consumers. Thanks to big data, organisations are able to create engagement and know what, how, who, when, where, to market their goods and/or services in the most effective way. Not to mention that this also creates a more personal experience for the consumer, and who doesn't love that!?

So, what do you think? Comment your thoughts on Big Data and its uses!