What is advanced analytics?

Advanced analytics is an umbrella term for a group of high-level methods and tools that can help you get more out of your data. The predictive capabilities of advanced analytics can be used to forecast trends, events, and behaviors. This gives organizations the ability to perform advanced statistical models such as “what-if” calculations, as well as to future-proof various aspects of their operations.

Some of the areas that make up the magic of advanced analytics include machine learning and artificial intelligence, semantic and graph analysis, data and text mining, complex event processing, pattern matching, predictive analytics, data visualizations, sentiment analysis, network, and cluster analysis, multivariate statistics, simulation, neural networks, and the list is constantly growing as new techniques are invented and adapted to the data analytics world.

Data mining, a key aspect of advanced analytics, is an automated method that extracts usable information from massive sets of raw data. Big data analytics are used for finding existing insights and creating connections between data points and sets, as well as cleaning data. Predictive analytics can use these clean sets and existing insights to extrapolate and make predictions and projections about future activity, trends, and consumer behaviors.

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What can advanced analytics do for me?

Because it involves so many disciplines and has such broad applicability, there are several excellent use cases for advanced analytics. Marketing departments can find a lot of value in these tools, as much of their work involves understanding consumer preferences and deciphering how they will evolve or what targets they might aim at in the future. This can help plan strategies and campaigns further in advance with more confidence and precision.

Inventory and warehouse managers can also benefit from BI tools that include advanced analytics. By understanding outflows and comparing them to sales, previous orders, and other datasets, they can expedite their ordering processes and reduce waste caused by purchasing inventory that won’t be sold or moved in short order.

See it in action:

Marketing Dashboard Example

Even manufacturers and other organizations that use machinery can employ advanced analytics to create self-maintaining systems as well as early reporting to prevent costly wear and tear. For these companies, creating early-alert systems can prove enough to help save thousands in repair and equipment costs.

Advanced analytics solutions

An advanced BI and analytics platform like Sisense is an essential tool for these teams, or any department, to simplify complex data into easy-to-use dashboards. Sisense uses advanced analytics solutions to connect disparate data in order to create an accurate canvas of your company’s operations — in real time, with its incredibly fast analytical processing power. Then, you can use those dashboards and visualizations to make reliable predictions and generate actionable BI insights on a deeper level.

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