by Sue Dunnell.
Business demands are accelerating, putting more pressure on IT to make quick decisions about change, be sure those decisions will be accurate, and that changes can be executed flawlessly.
Whether adopting new technology stacks, migrating to the cloud, or managing demand for support on the edge, it has become increasingly complicated to ensure you can rapidly recover from any unplanned outages and remain compliant throughout any type of change or transformation.
Enterprise IT organizations have all the data they need to execute on top migration projects, but it’s difficult getting value out of that data, because it’s locked in silos.
Not only is the data stored in different systems, it’s not normalized. There may be duplication of data as sources are not synchronized. Many products have seat-based licensing, limiting access to just a few resources. Different users have access to different systems, and no single user has access to all data.
Often there’s simply too much data, and IT teams can’t pull it together fast enough to make a good decision quickly.
Because the data is difficult to get access to, IT wastes time finding and acting upon suspect information, often not even knowing if a better source of data exists for the purpose at hand. This deepens the distrust stakeholders have in many decision support tools.
In addition to the problems the sheer volume of data can present, not having have an accurate picture of the interrelationships of assets and infrastructure across increasingly complex, hybrid environments can cause migration projects to stall out completely.
If IT expects to meet the today’s pace of change and break down the silos of data, it’s essential to have a dynamic decision support platform built for centralized collaboration and planning.
The platform should combine, normalize, and consolidate data from multiple sources into a single repository.
Once data is aggregated, decision making can begin.
All members of a project team should have a consistent view of the data set across business units, and be able to:
If IT is expected to meet today’s challenges, isn’t it time to demand such a solution?
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TDS CEO Mike Bullock shares blog posts written by our experts on how to think about, manage, and adapt to change in IT. These blogs share some of our best practices, customer experiences, and the many lessons we’ve learned along the way.
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Making decisions using data that is pieced together through a combination of spreadsheets, data exports, and email messages doesn’t provide project teams with a comprehensive understanding of compliance, security and other business requirements. That’s why TDS enhanced its rules engine, making it easy to write simple scripts that apply business rules to data, ensuring that the results will be aligned with business goals.
We continue to evolve TransitionManager’s capabilities, focusing first on what problem we are trying to solve for the customer. For enterprise architects and cloud professionals, finding the right information and leveraging the variety of tools available to plan and manage IT transformation projects is challenging and complex.
Transitional Data Services (TDS), a global leader in modernizations, and cloud and data center migrations, today announced TransitionManager 6.0. The new release includes enhancements to further automate complex hybrid cloud planning, decision-making, transformation, and migration. Together they enable customers to rapidly respond to cloud adoption, cyber preparedness, disaster recovery and digital transformation strategies.