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CrowdStrike Outage: Impact And Recovery

From grounded flights to stalled out supply chains, the recent CrowdStrike Windows outage caused major disruptions across the globe. Read on to find out how Gartner Peer Community members were impacted, and how they're responding.

CrowdStrike Outage: Impact And Recovery

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Community Posts

AI and Research in Marketing and Communications: How Are You Ensuring Quality and Truth Over Speed? As AI becomes embedded in our day-to-day marketing operations, from customer insight to content strategy, it’s clear we’re gaining speed and scale. But are we sacrificing veracity and quality of output in the process? One of the biggest challenges I'm seeing is the rise of hallucinated content in AI-generated research. - How do we ensure AI systems are surfacing trustworthy, contextually accurate, and well-sourced information? - Are we building enough verification layers into our AI-driven content and research workflows? - And how are you educating teams (and execs) to challenge AI outputs, rather than accept them at face value? - What frameworks, tools, or governance models have you adopted to maintain integrity and depth in AI-led research and insight creation? - Have you had success (or struggles) balancing speed vs. substance in AI-powered strategies? Your thoughts, examples, and recommendations would be incredibly valuable in helping others try to navigate this shift responsibly.

How do you think AI will disrupt business across industries? Add to my list: 1. Content creation 2. Photos and video production 3. Basic coding and debugging 4. Strategic analysis to be highly complimented

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We are looking into Purview for Data Catalog, Data Map capabilities. There were multiple threads ~1 year ago with less positive feedback.

Has things changed since then? Has anyone implemented in recent months and how was your experience. We are looking at data sources such as ADLS, Synapse, Power BI and number of SaaS softwares.

How will GenAI advancements disrupt traditional DocAI or Intelligent document processing landscape? Are there any emerging trends? Which use cases might be impacted?

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How important is it for a cloud FinOps tool to have cost allocation and data analysis capabilities?

Critical10%

Very important50%

Somewhat important24%

Somewhat unimportant10%

Not at all important2%

Unsure1%

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What do you think is the hottest trend in Data & Analytics now and major priorities for CDO in near future??

Connected Governance and Trusted Intelligence21%

Data on the cloud (Modernizing data landscape)60%

Data Fabric , Data Mesh and Data sharing capability57%

XOPs (Data Ops, ML Ops, DevOps)15%

Artificial Intelligence & Intelligent Apps/ Automation using deep learning, Generative AI25%

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Which tech conference do you intend to attend in person next year or have already participated in this year, and what motivated your choice?

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Which teams have a role in deciding which compliance technology to purchase?

Security45%

IT80%

Legal42%

Compliance (We have a dedicated leader)24%

Other1%

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Which pitfalls—model bias, false positives/negatives, data quality, regulatory constraints—often impede AI-based security tools, and how can they be mitigated in a financial-services context?

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Has anyone used Denodo to create an abstraction layer that contains semantic models driven by federated queries? If so, what has your experience been related to performance? Cost?

We use Microsoft PowerBI extensively at the company. Over 15,000 reports.
For our "corporate" reports, like financials or HR, we centralize those requests and attend them with my team.
We currently "extract" information from multiple systems (ie. SAP, SuccessFactors, CRM, etc...) and put in into a SQL Analysis Services. For interpreting the data we have a Semantics model in PBI.
The problem I see is we can't scale enough to comply with the reporting demands as the semantic model is "unique" and we end up having only one or two developers that can work at a time.
Anyone has an idea how to scale their PBI teams without having to redevelop the semantic model per report?

We are considering a scanning solution for detecting Personal Information (PI) in our data assets, mainly AWS S3, DynamoDB, Salesforce, etc. We need the solution to detect PI, identify the type (e.g., infotype), and optionally map it to our own PI categories. We are currently considering BigID. Do you have experience with this tool or any other tools that can help us scan across different data platforms and technologies?

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How many different tools (that you know of) does your company use for Data Analytics? Which one is your favorite, and why?

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We are interested in learning about the tools or applications your utility company uses to support Energy Efficiency Customer Programs (EECP). At Southern California Gas Company, we utilize a custom-developed software platform that supports approximately 100 uniquely configured Energy Efficiency (EE) programs, along with components of our other Customer Programs and Assistance (CP&A) initiatives. This application enables customers to enroll in EE programs and provides functionality for tracking and reporting the benefits delivered by these programs. The platform is hosted, maintained, and enhanced by our vendor, Launch. We would like to explore whether your utility uses a custom-developed solution, SAP, or another off-the-shelf product to support your EECP and CP&A efforts. And whether the application is hosted on prem or cloud? Any issue arises in handling PII data?

Can anyone share how you handle data archiving, especially when moving to the cloud? Our organization has never archived data before. I’m interested in learning about your approach, how you got business teams to classify their data and set retention periods, and how you managed risks like storage costs.

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What advanced identity analytics or continuous access controls is your organization using (or planning to implement)? Any lessons learned you can share regarding vendor selection or implementation?

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