数据管理新规则：在AI时代创造价值

The NewRules of DataManagement Creating value in the AI era Contents 3Introduction:Finding value in the data clutter4Chapter1:Data at the crossroads7Chapter2:Data management practices have fallen behind9Chapter3:The new rules of data management12Chapter4:Leaders play by the new rules15Chapter5:The symbiotic relationship of data management and AI17Conclusion:Getting your data house in order19Methodology20About Splunk Finding value in the data clutter Organizations have long followed the conventional wisdomof centralizing data into one place to unify visibility andbetter make sense of it. Although this practice offeredorganizations some control and visibility, data structuresbecame more complex. Consequently, data managementbecame more difficult, requiring strategies that wentbeyond simply centralizing data into one location. In anattempt to control costs and manage the explosion of data,organizations started expanding their storage locationswith a medley of hybrid environments, opening the door fornew sets of challenges. You know the paradox: drowning in data but starving forinsights. The adage was never more true than it is today. The right data fuels insights that help organizations inventbetter customer experiences, identify malicious threats,and improve countless other processes to strengthendigital resilience. The plain fact, though, is that cloudservices, connected devices, and AI are overwhelmingorganizations. And instead of thoughtfully arranging theirdata, they are stockpiling it like a garage cluttered withgardening tools, camping gear, and childhood memorabilia. We wanted to know how organizations are cleaning outtheir data garages (so to speak), so we surveyed 1,475 IT,engineering, and cybersecurity professionals across theglobe about their data management practices. We’ve basedthis report on our findings, revealing the best practices toensure data is on hand when you need it, while creatingmore value. We think there’s a better way. The new rules of datamanagement can help you realize your security andobservability objectives and advance your mission, whileyou also optimize costs and compliance. Keep readingto see what data management leaders do differently.Discover how to tamp down data complexity andmaximize its value in the AI era. Data at the crossroads The survey confirms what many organizations may have suspectedfor years — the exponential rise of data is giving way to increasedcomplexity that makes it more difficult to access, analyze, and securedata, as well as comply with regulatory mandates. This is why havinga sound and comprehensive data management strategy is crucial fordigital resilience. But here again, volume and too many siloed data stores get in the way.In fact, 67% of survey respondents cite data volumes and growth asa challenge when implementing their data strategy, surpassed onlyby 69% who call maintaining data security and compliance a topdata management obstacle. They agree that defining data tiers, costmanagement, and other activities were also obstacles. Organizations wrestling with these data management issues arealso feeling far-reaching business impacts. Sixty-two percent ofrespondents claim that difficulties with data management resulted incompliance failures (33%significant impact, 29%moderate impact),71% say they led to poor decision-making (40%significant impact,31%moderate impact), and 46% confirm they led to competitivedisadvantages (8%significant impact, 38%moderate impact). Data redundancy is also a serious dilemma for organizations tryingto stay afloat in a tsunami of data. Fifty-nine percent of respondentsreveal their current data management strategy hassomewhatworsened the rate of data duplication, and 20% say the problem issignificantlyworse. Breaking down the cost of data management now because more is at stake. Organizations risk potential fines andimportantly, collateral damage to their reputations and customers’trust if they fail to comply. And even long-standing regulations havebecome more expansive and demanding. The European Union’sGeneral Data Protection Regulation (GDPR), for example, requirescomprehensive visibility across an organization’s entire data andcustomer environment, and is likely one of the costliest regulationsto support from a data management perspective. While convenient, without the right overarching strategy andcontrols, these distributed storage methods spread across multipleclouds, data lakes, and other storage locations risk duplication,redundancy, and governance issues. What’s more, adopting multiplestorage options can create unintended complexity that may thwartefforts to understand and streamline costs — more than a quarter(26%) of respondents maintain they aren’t able to accuratelycalculate the ROI of their data management investment. Data management costs are on the rise for almost everyone.Ninety-one percent of respondents reveal they spent more on datamanagement this year than in the previous year. Resp