Read more about author Jeff Cherrington. The mainframe industry is at a pivotal moment in its history – the need for increased compliance requirements, the desire for tighter networks with customers, the growing cloud environment, cost pressures, the need for modern user experience, etc., all contribute to the growing need for mainframe modernization.  According to a recent report from Forrester, 67% of enterprise infrastructure technology decision-makers say that they use mainframes, over half…

Read more about author Kumaravel Ramakrishnan. Due to the pandemic, the last two years have drastically changed IT operations, especially corporate IT service management, delivery, and support capabilities. In order to gauge exactly how these operations have changed, in late 2021, a global IT service management survey, The State of ITSM: Two Years into the Pandemic, was taken by 437 IT professionals, the majority of whom were from the U.S., India, Australia,…

Read more about author Nahla Davies. As more and more companies start to use data-related applications to manage their huge assets of data, the concepts of data modeling and analytics are becoming increasingly important. While they typically rely on one each, they are two very distinct concepts.  Companies use data analysis to clean, transform, and model their sets of data, whereas they use data modeling to map out and visualize the…

Read more about author Steve Zagoudis. The hallmark of any successful Data Governance implementation is awareness. In the context of a large system integration project, we are talking about awareness of: 1) Data Quality expectations and metrics, 2) Enterprise Data Management plan, 3) Data Governance best practices, 4) data risk factors, 5) Data Governance framework, 6) data owners/data consumers, 7) Data Architecture principles, 8) data loss/confidential data requirements, 9) data inventory definition and…