
Knoa Software announced the beta version of Executive Dashboards for Knoa Experience and Performance Manager (EPM) version 7.1. Knoa EPM is also offered by SAP as the SAP User Experience Management (SAP UEM) application by Knoa.
Executive Dashboards enable C-level executives and IT professionals to visualize empirical metrics for the overall performance of an enterprise implementation of SAP solutions, charting user proficiency, engagement and adoption in areas such as:
- Business impact of error conditions
- Productivity loss due to changes in production environments
- Team and user performance scorecards
The interactive screens offered via Executive Dashboards are customizable key performance indicators (KPIs) and can be configured to create ‘what if’ scenarios to determine actual and potential cost savings as a result of improved user efficiency and effectiveness, as well as application performance.
“Our customers are deeply engaged with gaining an accurate understanding of the cost impact of errors and of degraded user performance. This understanding is critical in prioritizing improvement strategies for their key business metrics,” said Bogdan Nica, senior product manager and evangelist at Knoa Software. “By contextualizing the analysis of performance issues, CIOs and executive management can pinpoint pertinent, high-impact indicators and run what-if scenarios based on actual business costs.”
The Knoa Executive Dashboards are scheduled to be available in the fourth quarter of 2014 as an extension to the current Knoa reporting application for SAP BusinessObjects solutions, at no additional cost. These dashboards can be utilized with Knoa EPM and all versions of SAP UEM, including those for SAP GUI, SAP BusinessObjects Business Intelligence (BI) solutions, SAP NetWeaver technology platform, and the SAP Customer Relationship Management (SAP CRM) application.
The Latest
In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability...
While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...
Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...
As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...
AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...
Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...
A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...
IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...
A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...