NTT is a leading global IT solutions and services organisation that brings together people, data and things to create a better and more sustainable future.
In todayxe2x80x99s xe2x80x98iNTTerconnectedxe2x80x99 world, connections matter more now than ever. By bringing together talented people, world-class technology partners and emerging innovators, we help our clients solve some of the worldxe2x80x99s most significant technological, business and societal challenges.
With people at the heart of our success, NTT is committed to attracting and growing the best talent and providing an environment where everyone feels they can belong and their contribution matters.
Want to be a part of our team? Analyze NTT's Internal Cloud Costs & identify opportunities to to drive cost optimization in our Microsoft Azure Cloud Platform using data driven decision making. Analyze NTT' sustainability metrics and report against measures that impact them positively
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Setting the Scene:
Data ingestion and normalization in the context of FinOps represents the set of functional activities involved with processing/transforming data sets to create a common repository for your cloud cost management needs. In this context, data ingestion and normalization occurs when bringing together cloud billing data, cloud usage data, cloud utilization and performance data, on-premises CMDB or ITAM data, business-specific data, and other data points from a variety of cloud providers and IT data repositories to create a collection of cost and usage information which can be queried to support and enable the FinOps Capabilities.
Effective FinOps practice requires access to regular streams of detailed usage, utilization and cost data, which can be categorized and analyzed to drive decision making. Unlike the world of on-premises data centers, there is no shortage of data on cloud usage. Cloud vendors produce massive amounts of very granular usage and cost data on which to base a FinOps practice.
Monitoring platforms, security platforms, and business operations applications can also provide data that will inform on utilization, location, value and usage, oftentimes at similar levels of volume and granularityxe2x80xa6so while the issue many data centers experienced was a lack of detailed data, the challenge faced by cloud users is oftentimes that there is too much. An effective data ingestion and normalization strategy should strive to provide the FinOps team with the right combination of data from
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