Big Data Storage and Data Virtualization

whitePaper | October 5, 2022

As we assess the global business environment in the latter half of 2022, perhaps the best single word that describes the state of play is uncertainty. Planning for uncertainties is a significant part of what we, as business executives and individuals, do on a daily basis. In times of uncertainty, brands realize they must work even harder to retain customers and deepen relationships by delivering value and empathy at scale. As we analyze our uncertainties, we can take comfort and guidance from management guru Peter Drucker, who wrote that “strategy aims to exploit the new and different opportunities of tomorrow” (Managing in Turbulent Times, 1980).

whitePaper | April 19, 2023

Unplanned downtime is one of the most significant pain points for industrial manufacturers today, costing them an estimated $50 billion each year. The risk is even greater for process manufacturing, where a critical equipment failure could result in the loss of an entire batch, environmental hazards, or safety risks. The adoption of digital technologies, such as the industrial internet of things (IIoT), promises to mitigate these threats by forecasting equipment failures and catching faults before they lead to unscheduled shutdowns. However, in practice, several challenges arise when maintenance personnel and operations leaders work to implement an IIoT solution aimed at eliminating unplanned downtime.

whitePaper | April 18, 2023

The MIT Future of Data Initiative is leading a multi-disciplinary research agenda to design and stimulate the deployment of consumer-empowering and accountable systems to provide trusted, traceable uses of personal data on an ecosystem-wide scale. The Initiative has gathered together computer science and Internet policy researchers as well as leading commercial enterprises in financial services, payment technology, cloud platforms, insurance and other sectors to discuss current challenges and opportunities in privacy and data governance. Today’s modern privacy laws place appropriately high expectations on organizations processing personal data. At the same time, consumers report declining trust in those who handle their personal data and regulators around the world struggle with the scale of the enforcement challenge. We aim to identify and put into service technical infrastructure for enterprises seeking to handle personal data in a trustworthy and lawful manner with guardrails to enable the traceable, accountable, and scalable use of data.

whitePaper | December 29, 2022

At ServiceNow, protecting customer data is a top priority. Different customers have different use cases, so we provide a range of encryption options for maximum security and flexibility. This document provides an overview of these options and is broken into three sections:

whitePaper | November 15, 2019

Fault-tolerance is the ability for a system to remain in operation even if some of the components used to build the system fail. Even with very conservative assumptions, a busy e-commerce site may lose thousands of dollars for every minute it is unavailable. This is just one reason why businesses and organizations strive to develop software systems that can survive faults. Amazon Web Services (AWS) provides a platform that is ideally suited for building fault-tolerant software systems. The AWS platform enables you to build fault-tolerant systems that operate with a minimal amount of human interaction and up-front financial investment.

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.