Hadoop’s Limitations for Big Data Analytics

whitePaper | September 12, 2022

Clinical Data Management (CDM) evolved over the last two decades from managing data entered on paper Case Report Forms (CRFs) to managing data transcribed into Electronic Data Capture (EDC) systems. The Society for Clinical Data Management (SCDM) strongly contributed to this first significant CDM evolution through its Good Clinical Data Management Practice 1 (GCDMP©) Chapters first published in 2000 and its certification program for Clinical Data Managers2 subsequently released in 2004.

whitePaper | November 18, 2022

For decades, the lack of visibility into the health of our data has led to data downtime in companies around the world. When data is missing, inaccurate, or erroneous, data quality initiatives are doomed to fail, leaving enterprises at a privacy compliance and business disadvantage.

whitePaper | December 12, 2022

In August 2022, the California Office of the Attorney General announced a $1.2 million settlement with international cosmetic retailer Sephora for violations of the California Consumer Privacy Act. Following this announcement came a wave of questions about the regulator’s emphasis on the broad interpretation of the CCPA’s “sale of data” and adoption of the Global Privacy Control.

whitePaper | April 2, 2023

In this white paper, we share how The Alan Turing Institute’s AI for science and government (ASG) programme has been using collaborative and multidisciplinary data science and AI to help tackle climate change.

whitePaper | August 9, 2022

This report shows you how a data catalog can help you easily find and then use the data you need.

whitePaper | October 17, 2022

Today, massive amounts of data are collected, processed, and stored for a range of analytical purposes around the world. Every customer, device, transaction, email, and image leaves a data trail. At present, this data is growing too big, changing too fast, and becoming hyper distributed. The traditional ways of doing integration and analytics are no longer viable or scalable. It is not feasible to create millions of data pipelines and to continue moving large amounts of raw data to a data lake or a centralized data warehouse.