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Strategic advice & alerts to leverage data analytics & new technologies

Leverage data and the technologies that generate it, from IoT to AI/machine learning, wearables, blockchain, and more, to improve decision-making, enrich collaboration and enable new services.

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Executive Update

Transforming Business Processes via Big Data Strategies

by Bhuvan Unhelkar

Value is the main interest in big data. Extraction of value from big data transcends both analytics and technologies. Value is highly dependent on the “context” in which data is analyzed and used. The Big Data Framework for Agile Business (BDFAB) is my comprehen­sive approach to big data adoption, which includes (among others) a module on business process modeling (BPM) and business analysis (BA). This module considers modeling and optimization of business processes as highly relevant and crucial in deriving value from big data. 


Relational Databases vs. NoSQL Databases: The End of the One-Size-Fits-All Era?

by Bart Baesens, by Seppe vanden Broucke, by Wilfried Lemahieu

The “one size fits all” era, where RDBMSs were used in nearly any data and processing context, seems to have come to an end.


AI’s Potential for Disruption in Banking and Financial Services

by Curt Hall

Banking and financial services companies were among the first to apply artificial intelligence (AI) in strategic applications. Initially, this took place in the mid- to late 1980s in the form of expert and knowledge-based systems for credit and loan approval and mortgage processing, and so on, and then in the early to mid-1990s, when neural network-based applications for credit and bank card fraud detection, and profitability management, began to be deployed.

Executive Update

AI & Machine Learning in the Enterprise, Part V: Industry Disruption

by Curt Hall

Cutter Consortium is conducting a series of surveys on how organizations are adopting, or planning to adopt, artificial intelligence (AI) technologies. We also seek to identify important issues and other considerations they are encountering or foresee encountering in their efforts. Here in Part V, we look at findings pertaining to the industries and domains where organizations see AI having its most significant impact.


3 Ways to Waste Money on AWS (and How You Can Avoid Them)

by Frank Contrepois

In this on-demand webinar, Cutter Consortium Senior Consultant Frank Contrepois shares advice, forged from his experiences with AWS, on how you can avoid wasting money on cloud services by keeping an eye on — and acting upon — three things.

Figure 1 — A big data strategy question: where to position the analytics?

Positioning Analytics: A Big Data Strategy Question

by Bhuvan Unhelkar

Analytics can be performed at various points in the deployment of a solution. Certainly, there are situations where “localized” analytics may be more appropriate than analytics performed in the cloud, and still others where analytics on the organization’s network might be more appropriate. The location of analytics can also determine where and when to integrate data into the analytical solution.

Photo by Clint Adair

AI Seeing Broad Applications in the IoT Domain

by Curt Hall

In this Advisor, I describe some important AI developments we are seeing with the IoT.


Fog: Highly Secure Next-Generation Architecture

by Frank Michaud, by John Zao

In this Advisor, we examine how fog architecture addresses cybersecurity for next-generation networks.