Data Applications

Let end users take action based on Data Science insights in the form of interactive, flexible data applications.

What are Data Applications?

Data Applications quickly provide information to end users in an interactive way. By providing this information with a context, it enables end users to take immediate action.

In the background, Data Applications analyse large-scale data sets using modern Data Science technologies. 




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Data Applications versus Embedded Analytics

Despite the fact that traditional dashboards and Embedded Data Analytics have made data much more accessible in the past, they often remain primarily a data exploration tool.

Data Applications, on the other hand, are capable of explaining data: highlighting trends, extracting insights, and then making recommendations and taking action based on this.

Data Applications bring a dynamic, purpose-built user experience. Unlike embedded analytics, which are typically designed and delivered by product and BI teams, Data Applications are delivered by software and data engineering teams.

This goes hand in hand with the broader trend of data projects becoming more and more similar to software engineering, and more and more different from traditional BI & Data warehousing.



Disruptive innovation

What modern Data Applications have in common is their disruptive potential. They enable companies to create completely new business models, equip their operations with unprecedented levels of automation, and significantly improve their productivity.


Data Application Use Cases

Data applications provide rich, fast insights, along with the automation and integration that data-driven companies use to stay ahead of the competition. Primary use cases include:

  • Predictive Maintenance: by analyzing real-time streams from IoT sensors, Data Applications can foresee possible production delays and missing parts and take automatic action.
  • Real-time personalisation and recommendations: Data Applications combine historical and newly ingested data to deliver instant insights and recommendations proactively or during customer interactions.
  • Fraud detection: Data Applications can alert users to further investigate credit card transactions in response to a specific anomaly or event.
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