What is Interactive Analytics?

Statistics Definitions > Interactive Analytics

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Interactive analytics is an extension of real-time analytics that has the capacity to crunch through huge volumes of unstructured data at scale and at speed. It gives users the ability to run complex queries across complex data landscapes in real time. State-of-the-art Business Intelligence & Analytics systems allow you to understand problems in real-world data and help you to suggest and evaluate design solutions to tackle the problem.

Interactive analysis tools assist you in managing “big data” by augmenting your ability to manipulate and reason about it. For example [1]:

  • Well designed visuals can help you to identify patterns and form new hypotheses,
  • New interfaces can enable you to iteratively transform and model data subsets, rapidly assess results, and translate the resulting procedures to run on scalable backends.

In addition to handling a high volume of data, fast, interactive analytics can query stored data sets in an ad hoc fashion, whatever their complexity. Typically, queries of this kind can take time, but interactive analytics accelerates the process by going beyond standard tables to return results faster.

How Interactive Analytics Works

Interactive analytics takes a three-phased approach to deliver results quickly:

  • The first phase is called “data ingestion” where data is gathered from multiple sources and placed into a central repository.
  • The second phase, “data preparation,” processes the raw data into a format that can be analyzed.
  • The last phase, “data consumption,” enables users to visualize the processed data and ask questions that will generate insights.

All three phases happen in parallel so that users can get answers to their questions as quickly as possible.

The Benefits of Interactive Analytics

The benefits of using interactive analytics are numerous. Perhaps most importantly, it gives users the ability to make decisions based on the most up-to-date information available. It also allows for exploring different “what if” scenarios so that users can see how different decisions might impact the outcome. Additionally, because interactive analytics works with leading cloud-based data warehouses, it is both scalable and cost-effective. And last but not least, it’s easy to use! even non-technical users can get up and running quickly.

If you’re looking for a way to gain insights from your data more quickly and easily, then you should consider using interactive analytics. The benefits are many: you can make decisions based on the most up-to-date information available, explore different “what if” scenarios, take advantage of scalability and cost-effectiveness, and get up and running quickly – even if you’re not a technical user.


[1] Herr, J. & Kandel, S. Interactive Analysis of Big Data. Retrieved May 24, 2024 from: https://homes.cs.washington.edu/~jheer/files/p50-heer.pdf

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