Strategic advice to leverage new technologies
Technology is at the heart of nearly every enterprise, enabling new business models and strategies, and serving as the catalyst to industry convergence. Leveraging the right technology can improve business outcomes, providing intelligence and insights that help you make more informed and accurate decisions. From finding patterns in data through data science, to curating relevant insights with data analytics, to the predictive abilities and innumerable applications of AI, to solving challenging business problems with ML, NLP, and knowledge graphs, technology has brought decision-making to a more intelligent level. Keep pace with the technology trends, opportunities, applications, and real-world use cases that will move your organization closer to its transformation and business goals.
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In this on-demand webinar, Cutter Senior Consultant Lynn Winterboer shows you how to write user stories for a DW/BI project, and she explains how these user stories contribute to several key Agile principles.
This workshop provides a greater understanding of the Agile approach in the context of Data Warehousing and Business Intelligence projects.
What we need is a description of hacking that omits the good/bad distinction because, as this Executive Update points out, exactly the same activities can be positive or negative. This Update provides a judgment-neutral guide to hacking to help you understand what hacking is about and how to facilitate its use (for good) and prevent its misuse.
The pattern I propose for a service assurance architecture is based on ideas taken from the operations support system (OSS) developed in the 1980s and 1990s. The original OSS, created for the telecommunications industry, covered a broad range of subjects and considered networking systems. The pattern presented here narrows the scope of interest to service assurance and casts the OSS principles into the IT systems area.
A recent Cutter Consortium survey that asked 80 organizations (worldwide) about their plans for the Internet of Things (IoT) helps provide some insight into how organizations are responding to the introduction of the Apple Watch and the growing consumer use of smart watches in general.
SEPTEMBER 8, 2015 — ARLINGTON, MASSACHUSETTS
Figure 1 -- Key characteristics of digital intelligence.
I was recently discussing the possibility of writing up some success stories, about enterprise architecture initiatives in particular, with a young colleague who then asked me: "And do you have any anti-success stories to tell?" Leaving aside his interesting choice of words, perhaps unconsciously aimed at avoiding the dreaded word "failure," this made be think of several cases where my clients snatched defeat out of the jaws of victory, so to speak, and what lessons we (or our clients) can derive from them.
The data lake is an evolutionary development of the increasing need to process unstructured data and huge stores of structured and semistructured feeds from machine processes and automation. It needs to be integrated with existing database and data warehousing solutions, whose processing and output is essential to analytics tasks. At the same time, the data lake needs to conform to the structural and security requirements of the firm.