Judith S. Hurwitz

Judith Hurwitz is an expert in cloud computing, information management, and business strategy.

Articles & Books From Judith S. Hurwitz

Cloud Computing For Dummies
Get your head—and your business—into the Cloud Cloud computing is no longer just a clever new toy in the world of IT infrastructure. Despite the nebulous name, it’s become a real and important part of our information architecture—and tech professionals who ignore it or try to skim their way through risk falling behind rapidly.
Article / Updated 06-09-2020
Planning your hybrid cloud computing strategy is a journey, not a simple set of steps. The right planning strategy is imperative to getting your plan to be operational. So, you need to look at the technical components, the business strategy, and the organizational plan. You have to focus on bringing all constituents to have a common understanding of how the cloud provides an opportunity for success.
Article / Updated 06-09-2020
Many companies that have begun to move into the cloud don’t do a lot of planning. Executives in different business units began to use public cloud services out of frustration because of inefficiencies in the IT organization. Over time, the cloud has taken a front seat in the way the overall business is approaching their future of computing platforms.
Article / Updated 06-09-2020
SaaS applications rarely operate completely independently. Companies often have an IT landscape that looks something like this: SaaS for CRM, a second SaaS for human resources, in-house analytics hardware behind a firewall, and AI for testing. Much of this information is fed into their enterprise resource planning (ERP) system that may be housed in their data center.
Cheat Sheet / Updated 02-23-2022
Digital transformation is the mantra of many organizations. There is no debate about it: Cloud computing has changed the way businesses operate. Small and mid-sized organizations may be all in on the cloud, while large enterprises are a hybrid and multicloud strategy. The cloud is helping startups challenge industry stalwarts, while at the same time, traditional companies are changing.
Article / Updated 06-09-2020
The cloud is the most disruptive computing revolution of our times; fostering dramatic changes in both the technology we live with every day and the way we use technology to transform business practices. As organizations are forced to deal with more innovative competitors, it is imperative that management can implement change fast.
Article / Updated 06-09-2020
It’s important to understand the common elements required to make clouds functional. In this section, we give you the basics of what you need to know. The figure illustrates the related elements that come together to create clouds. On the bottom of the diagram is a set of resource pools that feed a set of cloud delivery services.
Cheat Sheet / Updated 02-09-2022
To stay competitive today, companies must find practical ways to deal with big data — that is, to learn new ways to capture and analyze growing amounts of information about customers, products, and services.Data is becoming increasingly complex in structured and unstructured ways. New sources of data come from machines, such as sensors; social business sites; and website interaction, such as click-stream data.
Article / Updated 03-26-2016
The best way to understand the economics of big data is to look at the various methods for putting big data to work for your organization. While specific costs may vary due to the size of your organization, its purchasing power, vendor relationships, and so on, the classes of expense are fairly consistent. Big data types and sources The most important decisions you need to make with respect to types and sources are What data will be necessary to address your business problem?
Article / Updated 03-26-2016
To fully understand the capabilities of Hadoop MapReduce, it’s important to differentiate between MapReduce (the algorithm) and an implementation of MapReduce. Hadoop MapReduce is an implementation of the algorithm developed and maintained by the Apache Hadoop project. It is helpful to think about this implementation as a MapReduce engine, because that is exactly how it works.