Analytics & Business Intelligence
IoT and Developing Analytics-Based Data Products
In this webinar, Thomas H. Davenport and Stephan Kudyba discuss the process of developing a new generation of data products.
In this webinar, Thomas H. Davenport and Stephan Kudyba discuss the process of developing a new generation of data products.
Providing up-front structure for data may reduce the need to process it — and limit distortions.
There’s a boom in using analytics for human resource decisions. Tenure decisions should be next.
Miscommunications between decision makers and data scientists are common. Enter the data translator.
HR analytics is the next big change in human resources management.
Live webinar with MIT SMR authors of “Designing and Developing Analytics-Based Data Products.”
A series of small errors in data can lead to major mistakes.
Video panel features a discussion of real-life cases: organizations becoming analytical innovators.
Developing and deploying successful analytics technologies means recognizing that the human factor is paramount.
Case studies from a range of businesses highlight how analytics requires organizations to evolve.
A new data tool from South Africa’s Nedbank helps its clients understand their customers better.
South Africa’s Nedbank uses analytics to help its clients reassess their customer relationships.
Many financial firms in South Africa are investing in analytics technologies and human capital to build capabilities that strengthen customer relationships and set the stage for long-term growth through data-driven services.
Many organizations are finding success with IoT projects with thoughtful planning.
The information economy is giving way to an economy focused on analytics-based data products.
AI’s value for managers lies in its ability to predict equipment failures and assess human emotions.
Digital transformation is just a step in the journey toward a cognitive technology revolution.
Our once-subservient machines are encroaching on tasks that have been firmly in the human domain.
While the financial services industry is increasingly turning to data and analytics, educating its non-quant managers is proving to be a challenge.
New research shows bias exists even in merit-based systems — but a data-centric approach can help.