Big data: The next frontier for innovation, competition, and productivity

whitePaper | May 27, 2021

In many organizations, we need more collaboration between businesses, analytic teams, application developers and IT operations. These teams often work with data in silos and end up duplicating efforts, failing to integrate, or missing opportunities to deliver value from data. In addition to siloed efforts, data scientists are also faced with ever-increasing volumes and speeds of data. And the reality is they’re expected to answer questions just as fast as - or faster than - before. It’s important that we’re using the right data and the right techniques to ensure optimal outcomes. Download this guide to learn more about SAS and open source.

whitePaper | November 10, 2022

In this hyper-competitive era, faster time-to-market plays a vital role in the success of an organization. Any lag accounts for the 'Cost of delay,' impacting the value a product could create otherwise. This is the primary reason teams are adopting an agile approach to software development, testing, and release. Unfortunately, teams that don't follow suit find it challenging to deal with this accelerated timeframe.

whitePaper | November 24, 2022

Without a data-literate team, your company doesn’t have a chance of becoming data-driven. “Speaking data” is one of the biggest skills in the coming years as more technical skills (think SQL or R programming) become embedded in the tools themselves, demonstrating what we’ve always known — that tools will only take you so far. Your real resource is people.

whitePaper | September 28, 2021

Read on to learn how the Cloudera Data Platform accelerates your on-premises data analytics operations in a manner reminiscent of the cloud, unlocking flexibility, scale, and power from your traditional, on-premises data center.

whitePaper | June 27, 2023

Data mesh is an innovative approach to data management that offers a solution to the most common challenges organizations face when dealing with large-scale data management. Data mesh concept consists of four key principles for large-scale data management in a multi-tiered, multi-domain organizational structure: domainoriented ownership, data as product, federated computational governance and a self-service data platform. These all promote a more agile, efficient and scalable data architecture. However, one of the central challenges to implementing data mesh is designing decentralized governance mechanisms that align with its core principles.

whitePaper | April 7, 2022

This white paper was created to outline best-practices for measuring, reporting, and building a constant stream of key performance indicators related to your physician network.