Published By: ServiceNow
Published Date: Oct 18, 2013
Certifying the accuracy of a CMDB with inconsistent, manual methods is unreliable. ServiceNow's built-in data certification gives you the ability to automate the process. Learn how data certification works with the ServiceNow CMDB to deliver a trustworthy single system of record you can rely on.
It is not uncommon for SAP system copies, including any post-editing, to take several days to complete. Meanwhile, testing, development and training activities come to a standstill, and the large number of manual tasks in the entire process ties up highly skilled SAP BASIS staff.
Enterprises are looking to automation as a way to accelerate SAP system copies and free up staff. However, this is only one part of the problem: What further complicates the system copy process is the need to safeguard sensitive data and manage huge data volumes while also ensuring that the data used in non-production systems adequately reflects the data in production systems so the quality of development, testing and training activities is not compromised.
This white paper explains how a considerable portion of the SAP system copy process can be automated using the CA Automic Automated System Copy for SAP solution and SNP T-Bone, helping enterprises become more agile.
"There's new legislation in place, that's expanded the definition of personal data and puts IT and testing departments on high alert to safeguard personal data, across testing and development environments. It's the General Data Protection Regulation (GDPR). Are you ready for it?
In this session, we’ll demonstrate how CA Test Data Manager helps to both mask your production data and to generate synthetic test data; a powerful combination to help you meet compliance needs and deliver quality applications. There will be a short section on the future of the tester self-service model that will enable testers to efficiently get access to the right test data."
Published By: DataFlux
Published Date: Jan 07, 2011
This white paper describes a general approach for planning your organization's efforts to improve data quality, providing a data-example-driven perspective of some of the unique challenges of product data quality, as well as discuss and demonstrate three critical steps to improving product data quality.
For data scientists and business analysts who prepare data for analytics, data management technology from SAS acts like a data filter – providing a single platform that lets them access, cleanse, transform and structure data for any analytical purpose. As it
removes the drudgery of routine data preparation, it reveals sparkling clean data and adds value along the way. And that can lead to higher productivity, better decisions and greater agility.
SAS adheres to five data management best practices that support advanced analytics
and deeper insights:
• Simplify access to traditional and emerging data.
• Strengthen the data scientist’s arsenal with advanced analytics techniques.
• Scrub data to build quality into existing processes.
• Shape data using flexible manipulation techniques.
• Share metadata across data management and analytics domains.
Electronics and Software Engineering are quickly merging with traditional Mechanical Engineering to create a new paradigm in auto manufacturing: Mechatronics. Industry experts predict that this shift will bring about profound advances in automotive product development. Unfortunately, existing IT and process infrastructures do not provide sufficient capabilities to support the new paradigm: multiple data silos, a lack of standardized processes, and integration issues on a tool level (Mechanical, Electronic, Software) continue to pose serious obstacles to development efficiency, and remain a frequent source of delays, quality issues and cost increases.
Businesses need to plan for unforeseen events that can disrupt productivity, impair the customer experience, and possibly even threaten a business’s existence. A disruption every business needs to plan for is any event that destroys valuable data, inhibits access to data, or causes downtime of core applications.
Consider the staggering amount of information your company stores electronically. What if an unforeseen event destroyed all financial records, client contacts, and application data? You wouldn’t be able to send customers accurate invoices. Your marketing efforts might be undermined. You would lack key metrics for measuring quality, profitability, and more. The losses could be staggering.
In every aspect of life, it’s smart to plan for unexpected events. That’s especially true for two plans every business must have: a disaster recovery plan and a business continuity plan.