What is advanced analytics? What are its applications?

One of the most exciting aspects of data analytics is its constantly evolving nature. What started off as analytics systems that could only analyse data to describe the current situation has evolved into advanced data platforms that can process petabytes of data to predict future trends. The proliferation of advanced analytics is one of the more exciting developments in this industry.

But, what is advanced analytics? What is its business value? That is what we will be explaining in this article.

What is advanced analytics?

As the name implies, advanced analytics can do far more than what the standard analytics software can do. Advanced data analytics refers to systems that go beyond the capabilities of standard BI and analytics. These systems enable data analysts to go deeper into datasets using machine learning, pattern matching, sentiment analysis and cluster analysis, just to name a few techniques, which cannot be done on earlier versions of the software.

Advanced analytics functions are different from conventional analytics systems. It incorporates classic approaches to analysing data with newer, more advanced machine-driven techniques, like deep learning. Data mining is a key differentiator that separates standard analytics and BI from more advanced solutions like machine learning, neural networks and data visualisations. These advanced methods find the patterns and correlations in big datasets, setting the groundwork for deeper analysis.

Advanced analytics holds a huge advantage over standard data analysis software because it leads to better, more reliable answers. These data analytics platforms can mine data at a deeper level than what standard BI can manage. While some solutions, like self-service BI, hold a lot of value for certain business functions, they cannot compare to the level of analysis provided by advanced analytics. These analytics systems feature quality-tested algorithms that are always updated to analyse data to reflect current and future trends. Capabilities that allow data analytics software to create a more accurate picture than before.

In addition to a deeper, more comprehensive level of analysis, there are also other benefits. Some of these benefits include creating superior data models and simplifying data preparation.

Furthermore, the right analytics software simplifies analysis. When using advanced analytics platforms, like SAS advanced analytics, data experts don’t need several software platforms to complete different types of analysis, like categorical data analysis and psychometric analysis.

As you can imagine, this makes it much easier for any data analysts to use the system.

There is no denying that advanced analytics offers several technical advantages, but how can businesses translate these technical benefits into systems that generate value?

The applications of advanced analytics

Corporations in different industries can use advanced analytics to conduct more sophisticated levels of analysis. For example, in marketing, instead of examining what is popular with customers at the moment, businesses can take it one step further to decipher how consumer preferences evolve, which can be used to refine marketing campaigns. Another example is manufacturing, where businesses can use analytics to create self-maintenance systems that reduce wear and tear. This is possible because traditional BI systems analyse data to examine historical and current trends, but advanced analytics examine data to predict future trends.

The supply chain can be easily automated to improve operational efficiency. While some decisions will always be in the hands of humans, advanced analytics can be trusted to make decisions autonomously without any human intervention. Certain parts of the production process, like inventory checking, can be handled by systems developed using advanced analytics platforms. Other functions like monitoring, data gathering and forecasting can be executed using platforms built from advanced analytics. Due to their architecture, this system can function with greater efficiency than their human counterparts, giving organisations the chance to make significant gains in productivity and efficiency.

An exciting, new era in data analytics

As data analytics becomes more prominent, we begin to embark on an exciting era where advanced analytics powered by machine learning and AI becomes the norm. When that happens, we are going to see organisations make significant gains in productivity and efficiency. This is because analytics systems can do so much more than before, they provide deeper insights into data that allow organisations to be more proactive in their operations, making it easier to cut costs, save time and create exciting new technologies.

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