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The heat is on. The tension in the kitchen is tangible as a team of chefs rushes to impress hungry guests on a busy Saturday night. Dozens of ingredients and cooking utensils are strewn across the kitchen, causing confusion and slow preparation. With so much to keep track of, problems are going undetected — as chefs rush to plate their dishes, a pot of soup boils over and leaves a puddle on the floor. The noise is overwhelming as pots and pans sizzle and clash, chefs shout incoming orders, and timers blare in unison. The kitchen is on fire, but each chef must maintain composure to keep customers happy.
As an ITOps professional, you’re not laboring over a hot stove in your day-to-day workflow, but this chaotic scene may still sound familiar as you deal with growing data volumes in your evolving digital landscape. Gartner predicts that large enterprises will triple their unstructured data capacity across on-premises, edge, and public cloud locations by 2028, compared with mid-2023. To be successful, your team needs to be able to make sense of all this data — because lack of visibility leads to slower detection, investigation, and response, resulting in costly problems like downtime, silos, and more.
So, how can you prevent these “fires” from happening in the first place? The answer is data management.
The heat is on. The tension in the kitchen is tangible as a team of chefs rushes to impress hungry guests on a busy Saturday night. Dozens of ingredients and cooking utensils are strewn across the kitchen, causing confusion and slow preparation. With so much to keep track of, problems are going undetected — as chefs rush to plate their dishes, a pot of soup boils over and leaves a puddle on the floor. The noise is overwhelming as pots and pans sizzle and clash, chefs shout incoming orders, and timers blare in unison. The kitchen is on fire, but each chef must maintain composure to keep customers happy.
As an ITOps professional, you’re not laboring over a hot stove in your day-to-day workflow, but this chaotic scene may still sound familiar as you deal with growing data volumes in your evolving digital landscape. Gartner predicts that large enterprises will triple their unstructured data capacity across on-premises, edge, and public cloud locations by 2028, compared with mid-2023. To be successful, your team needs to be able to make sense of all this data — because lack of visibility leads to slower detection, investigation, and response, resulting in costly problems like downtime, silos, and more.
So, how can you prevent these “fires” from happening in the first place? The answer is data management.
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