“Patty is a very talented sales manager. She has high levels of emotional intelligence which enables her to quickly win respect and build trust with senior executives. Her ability to help her teams build effective strategies to win major opportunities in complex accounts is extraordinary. With her help, I closed over $3M in new enterprise business within major industrial accounts within a 10 month period. ”
About
With over 30 years of experience in software sales, I have a proven track record of…
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Happy to share that I've earned my Generative AI for Productivity credential from Cornell University through eCornell. Looking forward to applying…
Happy to share that I've earned my Generative AI for Productivity credential from Cornell University through eCornell. Looking forward to applying…
Liked by Patty Collins
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16 Sales Methodologies Explained Visually Tired of Googling "what is SPIN" or piecing together half-baked summaries of Challenger, MEDDIC, or…
16 Sales Methodologies Explained Visually Tired of Googling "what is SPIN" or piecing together half-baked summaries of Challenger, MEDDIC, or…
Liked by Patty Collins
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What is your Product Management Personality? Ever wondered, "Am I even a real product manager?" Maybe you mostly deal with optimization or quality…
What is your Product Management Personality? Ever wondered, "Am I even a real product manager?" Maybe you mostly deal with optimization or quality…
Liked by Patty Collins
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5 people have recommended Patty
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PM vs PM vs PM: Is your company confusing these titles and roles? And becoming less effective as a result... When product managers introduce…
PM vs PM vs PM: Is your company confusing these titles and roles? And becoming less effective as a result... When product managers introduce…
Liked by Patty Collins
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The APAC Myth That’s Holding Companies Back I hear it all the time: “Australia can be our APAC hub.” I get it. I lived there for 10 years. Back…
The APAC Myth That’s Holding Companies Back I hear it all the time: “Australia can be our APAC hub.” I get it. I lived there for 10 years. Back…
Liked by Patty Collins
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Heather Hershey
It's been a productive week in digital commerce research at IDC. Here's a recap in case you missed it. To Excel in Commerce, OMS Vendors Need to Help Prospects Overcome Spreadsheet Dependency https://lnkd.in/gGEEz4vt Impact of CPQ on Revenue Recognition: Regional and Company Size Breakdowns https://lnkd.in/gp-_tBd9 Digital Commerce Market a Bellwether for Agentic Evolution of Enterprise Apps https://lnkd.in/gR-TajB3 BigSummit 2025: The Future of Commerce Is Channel Ubiquitous and Dominated by Emerging AI https://lnkd.in/gnT6iiD7 Commerce–PROS Partnership: Pricing Precision Meets Platform Flexibility https://lnkd.in/gzPUtbCX Got any recommendations for future research topics that I should investigate? DM me or leave it in the comments to this post. Happy Friday! #commerce #analyst #CPQ #OMS #revenue #AI
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Justin Borgman
Enterprise AI is accelerating, but succeeding in AI requires the right data architecture. Specifically, it requires a data architecture built for access and governance. I really enjoyed Rob Strechay's recent article following our recent conversation on AnalystANGLE. We covered a lot of ground, including how organizations are looking for concrete ways to implement AI strategies, and how that desire for praxis starts with choosing the right data architecture. The best data architecture for AI enables limitless access to data across their organizations, while also providing data governance they can trust. At Starburst, we believe the future of AI hinges on three things: 1. Data access that brings all your data to the table 2. Federated architectures that query data where it lives. 3. Data products that deliver data governance, ensuring that the right data is accessed by models and AI agents in the right way. Thanks to Rob and TheCUBE team for their insightful coverage. Read the full piece: https://lnkd.in/gypn22Uu #EnterpriseAI #DataArchitecture #Starburst #DataProducts #Iceberg #FederatedData #AIInfrastructure
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Protik M.
Yesterday at the Dallas Informatica User Group, we launched Atlas — Datacolor AI’s Informatica-based MCP platform. Atlas proves that Agentic AI adoption must be built on trusted data. It orchestrates IDMC policies and quality gates, logs outcomes for full lineage, and delivers one conversational UI across Informatica, Databricks, SAP, and Salesforce — all running in the customer’s own cloud. The strong reception validates our strategy: take horizontal accelerators, align them with global platforms, and deliver repeatable enterprise value at scale. This is Datacolor’s path forward: Agentic AI + Trusted Data.
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Greg Beaumont
I’ve just published a new article exploring strategies to unify data sharing across Snowflake, Databricks, and Microsoft Fabric. While consolidating onto a single platform is often ideal, the reality for many large enterprises is more complex. Team autonomy, legacy investments, and strategic diversification often lead to multi-cloud and multi-product environments. Can your cross-platform integration architecture become a strategic advantage? The article focuses on options to share delta parquet and iceberg format storage amongst the three platforms: https://lnkd.in/gs4nS8Tt In the real world, very few large organizations are unified on a single data and analytics platform. Snowflake, Databricks, and Microsoft Fabric are all very popular products with widespread adoption. All three offer lakehouse architecture tools, but what are your options if you have data in more than one of these products? How do you share data amongst the platforms in a way that minimizes replication, is cost efficient, and has low latency? This post is the first in a three-part series focusing on interoperability amongst Snowflake, Databricks, and Microsoft Fabric. #Snowflake #Databricks #AzureDatabricks #MicrosoftFabric
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Ravit Jain
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