software & applications |
|||
|
there are many reasons why the data underpinning these updates could be inaccurate . Sensors can transmit incorrect data or could be broken and delivering no information at all .
Without a process of regular data validation , sensor issues could take a few weeks or even months to spot , simply due to the volume of data created , the number of sensors in a facility and the fact business critical and supporting services are distributed across multiple data locations .
Validation from the beginning
The need for quality data will grow in importance as businesses adopt Internet of Things ( IoT ) technologies . As technology
|
develops and reports rely more heavily on data collected by machines , validating data needs to be a priority .
Simply collecting data is not enough . It needs to be analysed , cleaned and verified to convince decision makers and executives that reports on the data centre estate are accurate .
With assets this large , one error in data could result in service availability issues or potentially cause services to fail . In the early planning stages of a facility , a report containing incorrect data could mean budgets are spent on the wrong hardware or a data centre is built in an unsuitable location .
The operational performance of a data centre also depends on accurate data . Once a facility is up
|
The need for quality data will grow in importance as businesses adopt IoT technologies .
‘ The need for data is not going to wane , nor is the reliance on the data centre .’
|
and running , providing visibility and transparency into the data centre is important , especially as facilities become a greater part of business operations .
Energy , water , infrastructure – data accuracy is required to not only understand current performance and how to improve , but also to prove that the data centre is as efficient and as sustainable as possible .
When developing a hybrid data centre estate , making the correct decision without accurate information is absolute guesswork . Inaccurate information could mean investing in the wrong technology or moving data unnecessarily . The ability to analyse performance and ROI of cloud , colocation and edge computing investments is an even higher priority as data centre managers , and the organisation as a whole , are asked to prove that the decision to outsource was the correct choice .
One other crucial example – organisations also depend on accurate data to provide evidence for internal and external certifications they need to adhere to . If the information provided was found to be incorrect it could lead to certifications being retracted and embarrassment for the organisation .
The need for data is not going to wane , nor is the reliance on the data centre . This need will result in more analysis – of spending on analytics projects and of the data centre that powers them . Organisations are beginning to depend on advanced data technologies to power their business and it makes sense to validate this data for executive and shareholder confidence , and to avoid costly mistakes to a company ’ s public image .
|
March 2017 | 27 |