Scaling Data Science Capabilities - Leveraging HPCC Systems® to Build a Homogeneous Big Data Ecosystem

whitePaper | November 15, 2019

The potential of artificial intelligence to transform business performance is only now starting to be more widely understood in Financial Services. This is nowhere clearer than in the security domain, where the fusion of big data, advanced analytics and machine learning holds out the promise of startling improvements in cyber defenses through the introduction of Prescriptive Security.

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 | January 20, 2023

Organizations increasingly recognize that accountability through the implementation of a data privacy management program (DPMP) is essential to operate effectively in the modern digital economy. For many years, the focus of organizations in implementing a DPMP has been mainly to achieve compliance with data protection requirements. Today, many organizations have undergone a shift in understanding and realize that a DPMP is as critical for risk management and compliance as it is for enabling data strategy, building customer trust, winning business, and attracting company investment.

whitePaper | February 7, 2020

The problem is that growing volumes of data can lead to data paralysis, because no one knows quite where to begin or how to use it. Siloed information sources, no data management strategy, disconnected spreadsheets or analytical tools and poor data quality all work to compound the issues you’re facing.

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.

whitePaper | December 9, 2022

In Data Governance Methodology, we described why a modern active data governance methodology is superior to a traditional top-down methodology and how active data governance is supported by continuous improvement. We also discussed how a data governance process based on continuous improvement is a key component of a DataOps process.