By Swapnil Mishra - December 23, 2022 5 Mins Read
While unstructured data is challenging to manage and leverage, companies must go beyond legacy storage metrics. They must focus on understanding data and its utility for application owners, business stakeholders, and their role in data management decisions.
The humungous amounts of data being generated today have some serious records. According to current estimates, in 2022, the volume of data created every day will stand at 1.145 trillion MB per day.
Enterprise IT departments and data storage specialists face various challenges due to data explosion and data type diversity. These include rising storage and backup costs, complex management, security risks, and a visibility gap that limits opportunities.
In this, unstructured data is dispersed across numerous applications and storage locations inside and outside the enterprise, which is why it is more difficult to locate, move, and manage.
One of the biggest challenges of managing unstructured data is the issue of storing it safely and having a record of its volumes- in terms of specified metrics. These specifications need to move with the times. They include all relevant details that will allow enterprises and experts to study the volume of data in the context of current enterprise specifications.
Organizations need to move beyond traditional storage metrics and emphasize comprehending data and involving application owners, department stakeholders, and other business stakeholders in data management decisions.
These metrics should also track and improve energy consumption to achieve more general sustainability goals, which are crucial in the modern era of cyclical energy shortages and climate change.
The traditional IT infrastructure metrics mentioned above are prerequisites for any enterprise IT organization today. There are many new data-centric measures to comprehend and report on in today’s world, where data drives all decisions. Leaders of departments and business units are now frequently responsible for monitoring and paying for their data usage.
When business leaders are uncomfortable archiving or deleting their data, discussions with IT organizations can become tense. This is especially true when IT attempts to save money and free up capacity.
IT and departments can collaborate to make better decisions when they have visibility into data-centric versus storage-centric metrics. Due to the prevalence of data silos in businesses and the fact that data is dispersed across numerous applications and storage environments, including on-premises, at the edge, and in the cloud, these metrics have historically been challenging to collect.
Finding and indexing data across vendor boundaries, including cloud providers, using a single pane of glass is necessary to obtain this data. It is possible to compile data from all storage providers to get these metrics, but it is laborious and prone to mistakes when done manually. These broader and deeper analytics objectives can be attained with independent data management solutions.
Corporate sustainability initiatives and investments in new green technologies are being fueled by the global energy crisis, which has gotten worse by the conflict in Ukraine and the surge in demand from the post-pandemic economic recovery.
Responsible data management is a significant component of this overall project. Most businesses have hundreds of terabytes of data that can be deleted but is either hidden or isn’t understood well enough to be appropriately managed.
On top-performing Tier 1 storage (on-premises or in the cloud), storing infrequently used and zombie data is expensive and uses up the most energy. To slow down climate change, data centers must reduce their climate footprints. The data management metrics for sustainability listed below can be used to monitor and lower energy use.
It is true that putting time, effort, and money into new endeavors to broaden metrics programs. Then why do organizations choose it? For starters, having better and more detailed metrics on data can help decision-makers use it to manage data cost-effectively and sustainably, which can quickly reduce spending and energy use by 50% or more.
But there’s more: Access to comprehensive data insights will also benefit data consumers. The amount of time spent looking for data can be significantly decreased by understanding data and being able to quickly search for data characteristics like file type or metadata tags (like a project keyword). The correct data must be located and moved to the appropriate location, which takes up an estimated 80% of the time spent on AI and data mining projects.
There is always a need for quicker insights to solve complex problems, such as developing a new treatment for a chronic condition, improving the batteries in electric cars or wind turbines, or adjusting soil nutrients to produce a higher yield of crops. These sectors include healthcare, agriculture, government, utilities, and manufacturing.
Basic storage metrics are no longer sufficient to be competitive and achieve important commercial and operational goals in today’s data-driven economy.
Swapnil Mishra is a global news correspondent at OnDot Media, with over six years of experience in the field. Swapnil has established herself as a trusted voice in the industry, specializing in technology journalism encompassing enterprise tech. Having collaborated with various media outlets, she has honed her skills in writing about executive leadership, business strategy, industry insights, business technology, supply chain management, blockchain and data management. As a journalism graduate, Swapnil possesses a keen eye for editorial detail and a mastery of language, enabling her to deliver compelling and informative news stories. She has a keen eye for detail and a knack for breaking down complex technical concepts into easy-to-understand language.
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