Market trend

What’s advanced analytics all about?

| Author / Editor: Ahlam Rais / Ahlam Rais

Advanced analytics makes it possible to transform the huge volume of data into relevant KPI’s which can be followed in real-time and also allows one to predict future market trends, behaviour or events.
Advanced analytics makes it possible to transform the huge volume of data into relevant KPI’s which can be followed in real-time and also allows one to predict future market trends, behaviour or events. (Source: Deposit Photos)

Advanced analytics is extremely popular with organisations looking to excel in their business. The right business strategy implemented at the right time will most probably generate the right customer response and prove profitable to the company – this is what it’s all about.

Businesses around the world are constantly under tremendous pressure to make the right decisions for the growth of their company. Offering discounts during festive occasions, introducing a new brand, expanding production or even distributing freebies involve a lot of planning and money, that’s why it becomes all the more important that the initiative proves to be a success but how can one be sure? Forecasting the future through a crystal ball or reading horoscopes are not promising enough and this is where advanced analytics comes in.

Advanced analytics

What is advanced analytics? In simple terms, advanced analytics is the process in which huge amounts of data is analysed, thus deriving meaning from it and arriving at interesting facts which enable companies to make better business decisions with greater accuracy, efficiency and speed.

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Advanced analytics also makes it possible to transform the huge volume of data into relevant KPI’s (Key Performance Indicators) which can be followed in real-time and also allows one to predict future market trends, behaviour or events. Identifying the next best possible move for the firm in order to grow their business can also be determined.

Big data, predictive data analytics and data mining

Advanced analytics comprises of three core segments – Big data, predictive data analytics and data mining. Big Data plays an important role in the process and can be defined as large amounts of complex information that cannot be processed by traditional methods. Companies collect the data from internal as well as external sources and then process it by making use of advanced analytics. Big data comprises of structured and unstructured data. A prominent example of big data is the Google search index and Amazon’s product list.

Predictive data analytics makes use of current and past data to predict the result of a specific plan. For instance, online video sites make use of predictive data analytics and suggest videos that are likely to interest the viewer based on the selection of his past videos. Similarly, online shopping sites and other websites use the same strategy. It also applies to other scenarios such as how will sales be affected during a particular month or how will customers respond to a particular marketing campaign, etc.

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Lastly, data mining is the automated analytical method of extracting usable or valuable data from the massive data. Data mining utilises concepts such as Machine Learning and database tools to classify important parameters and trends for a particular situation. Supermarkets and retail stores use data mining to know the choices and preferences of their customers. This can also be applicable to service providers, science and engineering fields as well as educational institutions, and so on.

Generating potential opportunities

Advanced analytics is very effective however, before beginning this process it is extremely important to determine the objective of the exercise. If it is not clearly defined then one will not generate potential opportunities instead it will lead to failures. Thus, in a complex and ever-changing business environment, advanced analytics is vital to improve business decisions and make sure that they are ahead of their competitors.

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