Cloud computing’s promise of boundless scalability has a dark side: zombie data, those dormant datasets lingering unused in storage buckets, quietly inflating bills and carbon footprints. Soham Mazumdar, co-founder and CEO of WisdomAI, warns that enterprises overlook data as a prime culprit in escalating cloud expenses, with multiple redundant copies—from original records to ETL derivatives and experimental versions—piling up without purpose. "Data without a time value keeps piling up… so the direct ongoing effect on data storage, datacenter capacity requirements and the logical (negative) impact that has on any strategy designed to achieve sustainable GreenOps should be fairly obvious," Mazumdar wrote in a guest post for Computer Weekly.

Engineers, focused on immediate tasks like data transformation, rarely circle back for cleanup, especially when cloud storage feels cheap and creation is effortless. This waste extends beyond storage to compute and operations, undermining FinOps efforts to control costs and GreenOps initiatives for sustainability. WisdomAI, a data analytics platform bridging analytics, platform engineering, and operations, positions itself to track data "liveness"—identifying untouched datasets for archiving or deletion.

Recent funding underscores investor confidence in tackling this issue. In November 2025, WisdomAI raised $50 million in a Series A led by Kleiner Perkins, with Nvidia’s NVentures participating, following a $23 million seed round. The startup, born from Mazumdar’s experience at Rubrik, now serves clients like ConocoPhillips, Cisco, and Patreon, analyzing structured, unstructured, and even "dirty" data without LLM hallucinations by using large language models only for query generation, as reported by TechCrunch.

Elasticity’s Double-Edged Sword

Public clouds prioritize elasticity without quotas, unlike internal systems at companies like Google that enforced limits to prevent forgotten assets. "Public cloud environments prioritise elasticity but rarely impose limits. Resources expand automatically. Nothing pushes back when usage drifts or multiplies. You end up with idle storage, unused pipelines and zombie compute, racking up cost and carbon impact," Mazumdar noted in Computer Weekly. This leads to shadow IT and overprovisioned instances, with firms seeking tools for "rightsizing" and zombie asset hunts.

Platforms like Snowflake and Databricks exacerbate the problem, charging for forgotten queries and jobs. FinOps, the collaborative framework for cloud financial management, now intersects with GreenOps, which targets environmental impact through efficient resource use. "Cost and carbon are now inseparable… Every unnecessary copy of data, every idle workload, every forgotten pipeline carries both a financial and environmental cost," Mazumdar emphasized.

Industry reports highlight the scale: zombie data represents "durable waste" in storage, where providers profit from indefinite retention, as detailed in a December 2025 Medium post by FinOps Universe. Enterprises spend over 30% of IT budgets on storage, backups, and recovery, much of it on unused files from departed employees, according to Komprise’s reports.

FinOps Meets GreenOps in AI Age

Manual governance fails amid AI-driven experimentation, where temporary pipelines proliferate. Automation for liveness tracking—flagging months-inactive datasets—is essential. Tools like GitHub’s open-source Zombie Hunter scan AWS, GCP, and Azure for idle resources via Slack, estimating savings on snapshots and load balancers. At FinOps X 2025, Google touted over 1 million AI-enabled anomaly alerts, while Oracle added hourly emissions reporting for GreenOps compliance, per TechTarget.

Reddit’s r/FinOps community shares horror stories: laid-off employees spiking GPU bills 10x, caught only by anomaly detectors, or zombie GPUs draining wallets. Practitioners recommend multi-cloud tools like Cloudaware for idle EBS volumes and policy checks, integrating cost and carbon dashboards. "The combination of GreenOps and FinOps approaches can help monitor both costs and emissions," states The New Stack.

WisdomAI’s enterprise context layer learns from data patterns, enabling proactive insights over static dashboards. "Our mission now is to move from aspiration to operational reality… GreenOps stops being an abstract idea and becomes operational," Mazumdar concluded in Computer Weekly. AWS re:Invent echoed this, with CTO Werner Vogels noting "Cost is a close proxy for sustainability," linking the practices tightly, as per Forrester.

Tools and Tactics for Waste Warriors

FinOps tools proliferate: CloudZero for 100% allocation sans perfect tagging; Holori for multi-cloud visibility; Spot.io for idle VM recommenders. Open-source options like Grafana Cloud save teams thousands monthly by replacing pricier platforms. X discussions reveal practical wins, like Lambda functions halting dev instances after hours, slashing $4,000 monthly, or pausing idle Redshift clusters for $3,000 savings.

For zombie data specifically, Komprise identifies ex-employee files on NAS, moving them to cheaper tiers. Medium analyses distinguish zombie resources (noisy compute) from stealthy storage sprawl, urging automation to cut risk and costs. "Zombie data makes you pay indefinitely," warns FinOps Universe.

As AI inference sprawls, GovLoop advocates FinOps-GreenOps dashboards tracking cost-per-inference alongside carbon. Synyega notes AI’s varied deployment—SaaS, cloud, on-premises—demands converged practices to avoid unsustainable choices. WisdomAI’s growth to 40 customers signals market readiness for agentic analytics that govern data at scale.

Operationalizing Discipline

Enterprises must embed visibility and automation into data systems. Quota-like policies, AI anomaly detection, and liveness metrics transform GreenOps from buzzword to practice. With cloud bills ballooning—Meta tapping private credit for data centers, per ZeroHedge on X—ignoring zombie data risks existential threats.

WisdomAI’s trajectory, backed by $73 million total funding, positions it to lead. Clients tap it for queries like revenue forecasts, surfacing deal delays from telemetry and documents. As Mazumdar’s vision materializes, firms optimizing data waste will gain competitive edges in cost, sustainability, and AI foundations.