DRIVE MORE EVIDENCE-BASED BUSINESS STRATEGY WITH CUSTOMER ANALYTICS

whitePaper | February 10, 2022

Modern data governance leaders are searching for the role that governance should play in delivering high-quality data.

whitePaper | December 30, 2022

This white paper details Dell CloudIQ, the cloud-based AIOps proactive monitoring and predictive analytics application for Dell systems. It describes how it uses machine learning and other algorithms, notifications, and recommendations to help you optimize compute, storage, hypercoverged infrastructure, data protection, and network health, performance, and capacity.

whitePaper | August 25, 2022

Most organizations realize data governance is necessary - if not indispensable - for mitigating data risk while sustaining its longterm value. However, there’s still a fair amount of ambiguity around what exactly data governance is and how to best implement it. By definition, data governance is an enterprise-wide initiative for formalizing the processes, people, and protocols for using data. It reduces risk while increasing data’s ultimate value: consistent reusability for achieving mission critical objectives. Data governance is a strategic approach for creating unassailable trust in data throughout the enterprise.

whitePaper | June 16, 2022

It seems like the business world has gone crazy for machine learning (ML) and artificial intelligence (AI), viewing the technologies as the essential keys to the very future of the enterprise. In fact, a recent survey from ESIThoughtLab found that two-thirds of business leaders see AI as critically important for their future. And yet, the respondents report that only 25% of AI projects are in widespread deployment and 40% of all projects are generating negative or no returns.

whitePaper | March 12, 2020

In recent months, my company (Baron Consulting) has been proactively involved in setting up Data Collection Systems for a range of Private and Public Organisations we are servicing. Some of the data collection challenges have already been discussed in our recent Raw Data Collection 2020: Principles and Challenges White Paper. While the RDC (Raw Data Collection) paper analysed the current state of the everchanging Data Collection requirements, it did not have the scope to address technicalities of the RDC processes along with the specific Data Collection tools and methods. The purpose of this paper is to fill the void by looking into implementation of the automated data collection processes.

whitePaper | April 7, 2021

Assembling the perfect data stack is impossible. But for most data teams, the path to leveraging rapidly evolving tech and best-in-class tools is even more difficult when it’s impeded by the pitfalls of monolithic legacy applications.