Data science is the application of scientific techniques and mathematics to making business decisions. More specifically, it has become known for the data mining, machine learning (ML) and ...

1. Advanced analytics applications provide the tools required for cleansing, contextualizing, and analyzing large and complex data sets to create insights. Courtesy: Seeq ...

Third-party vendor applications are integrating AI capabilities, yet companies frequently lack full visibility or control ...

These days, data managers have an embarrassment of riches when it comes to the platforming, storage, and provisioning of data and associated analytics applications. However, selecting the right ...

Both data warehouses and data lakes offer robust options for ensuring that data is well-managed and prepped for today’s analytics requirements. However, the two environments have distinctly different ...

Analysis How Data Analytics Can Drive Damages Calculations This article reviews three real-world examples of data analytics in action, showing how mining structured or unstructured information can ...

Users get frustrated when basic data analysis capabilities prevent them from aggregating their own data or creating visualizations. Embedded analytics helps application development teams to innovate ...

The potential applications of synthetic data in finance are wide-ranging and impactful. Here are some key use cases where synthetic data can make a significant difference.

Eyal Eliakim, Practical Applications of Data Analytics in Professional Football, Movement: Journal of Physical Education & Sport Sciences / בתנועה: כתב-עת למדעי החינוך הגופני והספורט, Vol. 11, No. 3, ...