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Tech companies in an array of areas are quickly adopting big data to uncover relevant trends. They then use this data to make crucial business decisions. However, before these effective decisions can be made, sourcing the data is the first step and of significant importance.
All companies who want to maximise their use of big data must content and navigate the best ways to source and mine it. From analytic experts in Silicon Valley to gaming analysts situated over the big pond to the creative office at InTouch Games – everyone is involved. These businesses are looking for the most effective and simple methods of mining data. Here are the techniques they are using.

Identifying Patterns
Tracking the patterns of service users and those that buy your products is one of the most important techniques. Without this data, you cannot be sure of your market and your brand’s representation. Naturally, this feeds into marketing, product design and even your website. It also helps you identify anomalies.

Looking out for Anomalies
Looking for data that does not fit in with the rest may seem an unproductive and ineffective discovery. However, these anomalies may lead to a whole new market. For example, if one company predominantly sell their products to older males but then see a rise in female buyers, this may redirect marketing campaigns to make the most of a potential new audience.

Classifying Data
Classifying data is when large amounts of data are grouped into different categories. This enables analysts to understand the different elements of the dataset and can give insights into customer behaviour. To get to this point analytics experts will use statistical tests or qualitative techniques. This method may appear simplistic from first glance, but it is often slightly more complex than first expected.

Prediction is exactly as it sounds. Companies will predict how their market will behave based on previous actions that are sourced through the data. However, this method is not just to predict actions, it is also used to anticipate threats. Predicting future behaviours and outcomes is not a new phenomenon among companies. However, due to the birth of big data, these predictions are now much more accurate and offer fewer risks.

Another way to forecast behaviours is regression analysis. These sorts of tests are the first that statistics students are confronted with. They look into the relationship between two variables and predict what will happen if one of those variables is changed. This allows for a simple but sophisticated method of exploring business options.
These are just some of the basic ways that data mining is being carried out. Savvy analysts and analytical gurus are capable of deploying advanced mining techniques, but still call on these fundamental methods. The development of big data and sourcing data is expected to advance in the near future, meaning businesses will have to continue to adapt, while also being mindful of data regulations.

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