by Sue Dunnell.
According to Gartner, poor data quality costs organizations an average of $13.3M per year. Worse, 39% don’t know what that bad data is costing them, as no one is tracking the impact.
Harvard Business Review found that 18% of businesses connect to over 15 data sources and 9% have no idea how many sources they are currently pulling data from.
Even more depressing, 40% of businesses will fail to achieve objectives due to poor data quality.
IT leaders need to have information at their fingertips to make a variety of critical decisions every single day. Whether providing input for a strategic project, responding to an executive inquiry, or doing quarterly planning and budgeting, IT is dependent upon accurate data.
And yet, getting accurate, relevant and actionable data is often the biggest challenge IT faces.
That’s because enterprise data is collected by different teams at varying intervals and stored across different systems, in multiple formats, which means it has inconsistent levels of freshness and accessibility. Few organizations have a single, consolidated source of accurate, normalized data.
It’s a recipe for failure and the risks of making poorly informed decisions can be significant to your business.
You should be able to ingest data from CMDBs, DCIMs, databases, and file based systems. An ETL engine normalizes data, and then stores it in an internal repository that can be accessed by any user across an organization. Business units can add key data points, or business facts, that need to be tracked for every type of asset.
We recommend that you have a visual, interactive mapping of all workloads, applications, servers, storage, and other assets. It allows you to easily expose inter-dependencies, and edit and make changes. Hosting sites can be explored quickly to identify performance bottlenecks, rogue hardware, and highly distributed systems.
Collaborate across business units with a consistent view of data for better decision making. Consider business facts, incorporate strategy and policy goals when planning, and analyze which options meet goals best. Integrate with existing assessment tools to leverage cost optimization, performance, and other metrics into decisions.
Basic Asset Information
“What if” Planning & Analysis
|What is the name of the asset and who owns it?||What are the security, governance, compliance and data requirements for every asset?||How many workloads with < 3 dependencies can be migrated to the cloud in the next 12 weeks, what would immediate cost savings be over next 12 months?|
|What are the dependencies across other assets?||Which applications can be offline during and end-of-month tech refresh?||Which business units are affected by regulatory requirements if we open an office in Europe?|
|Where is it located – on prem, public cloud, private cloud?||What is the criticality level of each application to business?||Which business units have highest adoption of microservices?|
|What kind of asset is it – workload, application, server, storage, other device?||Which applications have an RTO/RPO of less than 3 hours?||What is the risk to operations if core infrastructure has to be replaced?|
|Is it virtualized?||Which applications are tier 1 and what is the recovery plan if there is an outage?||How many systems will be impacted with implementation of a new security policy?|
|What platform or operating system does it require?||Which assets have HIPAA, PCI or other regulatory compliance requirements?||Will it be more cost effective to lift-and-shift legacy applications to the cloud or keep them in current data center?|
Built by practitioners who managed large, complex IT projects where there is zero tolerance for failure, TransitionManager helps IT eliminate risk and accelerate change in any size project or task. It provides IT with accurate data, visualization of dependencies across assets and infrastructure, and the ability to analyze and plan collaboratively across business silos.
By integrating with data sources, files, ITSM, SAM, monitoring, assessment, and automated move tools, TransitionManager lets you build a custom toolchain out of the products you already use and leverage the skills and expertise you already have. And, it unleashes data from silos so you can make better decisions and accelerate change.
The methodology and tools you choose for your migration journey will directly impact your goals and measure of success. Download our Data Center Migration Survival Guide now to kick off your journey.
Follow these key cloud migration best practices for successful cloud adoption in your organization.
When executing a cloud strategy it takes time to understand how your apps work, identify those most critical to business, which are best fit for the cloud, and which require modernization before migrating. What if you could accelerate this process by automating your toolchain?
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.