Context
SAP is one of the largest companies in the world, providing enterprise software for e.g. resource planning. This dataset consists of their official press releases since the beginning of the 2000s, which are currently available at https://news.sap.com/press-room/.
Content
Each item consists of a headline, describing the respective title of the press release. The data has been labeled in a weakly supervision manner into the following categories:
Partnership
: when the press release is mostly about a joint work or collaboration of SAP and another company, e.g. "SAP and IBM Collaborate to Serve Transportation and Logistics Industry"
Award
: when SAP or one of its subsidiaries has been awarded, e.g. "SAP Recognized as a Leader in Gartner Magic Quadrant for Manufacturing Execution Systems and Ranked #1 in ARC Advisory Group MES Market Research Study"
Financials
: SAP Announces Preliminary Fourth Quarter and Full Year 2016 Results
People
: press releases dedicated to e.g. hiring of Chief X Officers, such as "Jonathan Becher Named Chief Digital Officer and Leads SAP Digital; Maggie Chan Jones Will Join SAP as Chief Marketing Officer"
Solution
: releases about e.g. new solutions or tools and frameworks, such as "SAP App Center Simplifies Acquiring and Managing Partner Solutions"
Merger / Investment
: when SAP has bought or invested into a company, e.g. "SAP Completes Acquisition of Concur"
Story
: when SAP released stories such as case studies or success stories, e.g. "SAP Broadens Its Developer Community Engagement With Code for America Sponsorship"
Acknowledgements
This data is collected from publicly available SAP resources.
Inspiration
Why don't you try out to classify each headline into a specific label? This could help analysts a lot to stay up-to-date for the most important press releases. Or analyze topics within certain clusters.