Speeding Analytics with Spark, Data Lakes and Change Data Capture
Powerful new engines such as Apache Spark can drive real-time transformation and analysis of operational data from customers, transactions, supply chain events, and myriad other sources that feed modern data lakes. Change data capture (CDC) can also play a big role in getting data into the pipeline and data lake at the speed necessary for modern operational reporting and analytics.
August 28, 2018
The Three Pillars of Data Governance: Compliance, Trust, and Transformation
Many organizations initiate data governance programs because of pressing compliance issues that impact data usage. At the other end of the spectrum, some organizations begin by governing data that’s shared broadly through a community of consumers across the enterprise, each with their own perspective on what constitutes quality and usability.
August 30, 2018
Putting Data Governance at the Heart: Shortening Healthcare’s Path to AI
Organizations in healthcare and other industries are putting a priority on generating high-quality, data-driven insights for reducing costs, increasing quality, adhering to regulations, and building better patient relationships. Yet, that’s always easier said than done, especially as the complexity of collecting and integrating data only rises with time. In the healthcare industry, providers and payers are facing dramatic changes that affect every aspect of their businesses, from patient care to clinical cost management to payments to regulatory reporting and auditing. At the same time, competitive pressures from new players entering the industry—from retail, technology, and other sectors as well as digital start-ups—mean that to survive and prosper, organizations need to gather, integrate, and analyze more and different types of data.
September 11, 2018
Improving Data Sharing Through Modernized Data Accessibility
Organizations have struggled to easily provide access to sharable data assets ever since the early days of decision support systems. Traditional methods of data sharing are slow and cumbersome. Simple data sharing methods—such as emailing extracted files, opening up unsecured access to critical databases, or file exchanges via FTP or EDI—not only pose risks of inadvertent data exposure, they also fundamentally require manual steps for both the individual sending the data and the individual receiving the data.
September 12, 2018