Name: Know Your Enemy: Vulnerability Data And What To Do With It
Start: 2023-08-28T20:48:00Z
End: 2023-08-28T20:48:28.000Z
Location: BrightTALK

With more than 35 million users, Anaconda is the world’s most popular data science platform and the foundation of modern machine learning. We pioneered the use of Python for data science, champion its vibrant community, and continue to steward open-source projects that make tomorrow’s innovations possible. Our enterprise-grade solutions enable corporate, research, and academic institutions around the world to harness the power of open-source for competitive advantage, groundbreaking research, and a better world.

As financial services become increasingly data-intensive, traditional tools like spreadsheets often can't keep pace with growing datasets and complex analysis requirements. 
Hear from John Wengler, Executive Director at the Canadian Imperial Bank of Commerce (CIBC), who streamlined his workflows and significantly reduced his work time using Python and Anaconda. He will share how he successfully navigated the challenges of driving innovation while maintaining governance in a traditional corporate environment. Discover how teams can use Anaconda to tackle complex data challenges with improved workflows, achieve meaningful cost savings through automation, and build proof-of-concept models with secure Python packages.

Key Takeaways:
How financial services teams can manage complex datasets, automate workflows, and combine disparate data sources using Python—even in risk-averse environments with limited IT resources
Real-world strategies for addressing internal audit concerns and gaining buy-in for Python adoption
Overview of Anaconda's enterprise solutions for financial services: secure package management, governance tools, and collaboration features that scale

Driving Innovation with Python in  Financial Services

AI works in your environment…but not in production. AI development teams face critical open-source challenges: security vulnerabilities, complex dependency management, license compliance risks, and reliability challenges. See how Anaconda's trusted, curated packages natively embedded in Snowflake's Python workflows can accelerate time to value while reducing deployment risk. Access Anaconda's secure, curated repository in Snowpark and Snowflake Notebooks for open-source access, easier package and repository management, simplified security and trust and consistent environments that get you from experimentation to deployment to trustworthy outputs. Hear from Anaconda and Snowflake speakers and see a live demo of this integration in action.

What you'll learn:
• Current market context: why AI adoption stalls (environment conflicts, security risks, experimentation-to-production gaps)
• Why cohesive package distribution matters for AI reliability (examining dependency complexity in real ML stacks)
• How the Anaconda-Snowflake integration accelerates production deployment while maintaining security and compliance

Enterprise-Ready AI Development with Anaconda and Snowflake

Financial institutions face an unprecedented challenge: deploying AI at startup speed while
maintaining bank-grade security and regulatory compliance. The native integration between
Anaconda and Databricks is designed to address the trade-off between innovation velocity and
enterprise security. Join Databricks, Anaconda, and ESG as we review the current state of AI
deployment in financial services and share examples of the challenges and how this unified
platform scales from secure development environments to enterprise production, enabling
financial services to innovate quickly and confidently without compromising regulatory
standards.

From Pilot to Production: AI Governance Strategies for Financial Services

While enterprise AI offers tremendous potential for organizations, implementation challenges include rapid technological evolution and governance concerns that undermine innovation confidence. This session focuses specifically on AI governance and security, featuring Anaconda's practical advice and best practices for establishing trust controls over AI models and procedures to help organizations succeed with their enterprise AI initiatives.

Practical Open Source AI: Moving Fast Without Breaking Things

Enterprise AI projects are failing at alarming rates. Despite massive investments, most organizations struggle to move from proof-of-concept to production-scale success.

The problem isn’t the technology—it’s the approach.

Join Forrester Principal Analyst Mike Gualtieri, Forrester Senior Consultant, Luca Son, and Anaconda Field CTO Steve Croce as they reveal why some enterprises are thriving with AI while others remain stuck. You’ll discover the real barriers blocking AI success and the practical strategies that are delivering measurable results.

Key Takeaways:
The 3 critical mistakes that doom AI projects before they start
How to balance innovation speed with enterprise security requirements
The unified platform approach that eliminates AI toolchain fragmentation
Why curated open source beats DIY for production-ready AI at scale
 

Whether you’re a data leader frustrated by slow progress, an IT executive balancing innovation with security, or a business leader demanding AI results, this session provides the clarity you need to move forward with confidence.

Making Enterprise AI Work

Register to access this free on-demand webinar for an exclusive look at the latest enhancements to the Anaconda AI Platform—the only unified platform designed to streamline AI development with open source. In this session, Saundra Monroe will demonstrate how our unified platform empowers technical teams to accelerate innovation, reduce operational costs, and gain competitive advantage—all while maintaining enterprise-grade security and compliance.

Discover how the Anaconda AI Platform now delivers:

3X more compatible artifacts to launch AI initiatives faster
Simplified enterprise adoption with guided onboarding and smarter navigation
Curated environments tailored to specific use cases and industries
Comprehensive security and governance across your entire AI development lifecycle

Accelerate Innovation with the Anaconda AI Platform

The growth of open-source AI in the enterprise has been nothing short of phenomenal. Enterprise Strategy Group (ESG) research found that 99% of organizations are actively using, exploring or experimenting with AI in their environments.

As organizations accelerate their AI initiatives, the adoption of open-source tools has become essential. But there isn’t a commonly known playbook for how to leverage open-source AI, and rapid changes in AI models, tools, and frameworks means there is currently a steep learning curve. 

In this exclusive webinar, open-source visionary and co-founder of Anaconda, Peter Wang, shares insights about the growth and challenges of the open-source AI phenomena with Mark Beccue, ESG Principal Analyst. Tune in as the pair unpack:
• How open-source tools provide unparalleled flexibility, cost-effectiveness and access to cutting-edge tech
• Best practices for operationalizing AI with open-source tools
• How to overcome the AI readiness gap 
• Where & how Anaconda assists customers in their AI journeys

Understanding the State of Enterprise Open-Source AI & Adoption Challenges

Are you ready to revolutionize your data analysis workflow? Join us for an insightful webinar where we’ll explore how to streamline your analytical tasks using Snowflake Notebooks and Anaconda packages. Whether you’re a data scientist, analyst, or engineer, this session will equip you with the tools and techniques to automate repetitive processes, increase productivity, and gain deeper insights faster.

Automate Your Analysis Tasks with Snowflake Notebooks & Anaconda Packages

Join this webinar for an introduction to Python in Excel including taking your first steps, understanding data types and output modes. A brief introduction to Pandas DataFrames, custom functions and a simplified Python charting experience using the Anaconda Toolbox for Excel.

Introduction to Python in Excel

Experience our exclusive 2025 AI Predictions Webinar where top experts from Anaconda and the industry explore the trends, innovations, and opportunities shaping the future of AI.

What You'll Learn:
AI Agents: How autonomous agents will drive automation and business operations
AI Trends for 2025: What cutting-edge advancements to prepare for
Real-World Applications: How organizations are turning AI insights into action
Practical Advice: How businesses can align their AI strategy for the coming year

Moderator: Kodie Dower, Sr. Marketing Communications Manager, Anaconda

Panelists:
Peter Wang, CAIO, Anaconda
Greg Jennings, Head of Engineering - AI, Anaconda
Priyanka Kulkarni, founder and CEO of Casium

2025 AI Predictions: Uncover the Future of AI with Industry Experts

Join us for an insightful fireside chat as we peer into the future of artificial intelligence (AI) in 2024. In this dynamic session, industry experts will share their predictions and unveil the vast opportunities ahead in the rapidly evolving landscape of AI. Our speakers will delve into key areas shaping the AI ecosystem, exploring recent advancements in machine learning, large language models (LLMs), and beyond. Studying transformative breakthroughs to emerging trends, we will analyze the forces propelling AI innovation and their potential impact on industries ranging from healthcare and finance to manufacturing and entertainment.

In this webinar, you will learn:

What could be next, after this year’s explosive growth of large language models (LLMs)
Strategic considerations for organizations and data professionals navigating the AI landscape in 2024
How open-source AI and closed-source AI will compete in the coming year and the potential outcomes of the race to build marketable AI systems

AI in 2024: Unveiling Predictions and Seizing Opportunities

MLOps offers ways to optimize processes, automate workflows, detect anomalies, reduce costs, and improve business outcomes. However, implementing and applying these techniques can be a large and complex effort. In this webinar, we’ll explore how to successfully implement MLOps across the enterprise using data science platforms to achieve different business goals, like deployment and automation, reproducibility and scalability, diagnostics, governance and compliance, collaboration, and monitoring.

Speaker: 
Chris Styduhar is the Director of Enterprise Products at Anaconda. With a background in software engineering, machine learning, and enterprise technology solutions, Chris manages the development of Anaconda’s Data Science Platform, including MLOps and AI features that help data scientists build, collaborate, and deploy more effectively.

Data Science in the Enterprise: Leveraging MLOps in the Enterprise

Open-source software (OSS) is at the heart of many of the innovations in machine learning (ML) due to its accessibility, flexibility, and active community support. As a result, many enterprise organizations are adopting or seeking to adopt OSS into their operations, product development, and marketable solutions. However, as with any software, OSS is not immune to vulnerabilities and requires an actively managed governance program.

In this webinar, we describe some of the major advantages of open-source software, along with common risks. We also describe key features of an effective OSS governance program with a focus on challenges for enterprise in the areas of software supply-chain security, license management, and support.

Building an OSS Governance Program for ML in the Enterprise

As data continues to grow at an exponential rate, businesses must find ways to leverage it for competitive advantage.

In today's fast-paced environment, organizations need a solution that provides the resources, horsepower and scalability needed to create and execute complex, powerful AI / ML solutions.

An enterprise data science platform is the solution to enable organizations to efficiently manage their data and transform it into actionable insights. 

Join Anaconda's Director of Enterprise Product, Chris Styduhar, on Thursday, June 8 to learn:

The most compelling use cases for your data

Why your organization could benefit from a full-featured Data Science Platform

The unique capabilities provided by Anaconda's Data Science Platform and Enterprise products

Why You Need a Data Science Platform

Recent events have highlighted the importance of software supply chain trustworthiness and security.

In this session, we discuss the content trust features in conda and the Anaconda Professional Repository. We’ll describe the design of conda's package signature verification functionality and its trust architecture, and identify the threats they protect against. Finally, we’ll highlight what’s next for Anaconda content trust as we continue to work to better secure the conda package ecosystem.

How Conda Signature Verification Secures Your Software Pipeline from the Start

AI techniques like machine learning (ML) and deep learning (DL) offer new ways to optimize processes, automate workflows, detect anomalies, and reduce costs in manufacturing industries, with a potential value estimated at $2 trillion. However, these techniques can be tricky to implement and apply, with many potential pitfalls for the unwary.

In this webinar, we’ll explore some use cases for AI in manufacturing and highlight what data science and machine learning practitioners need to consider when applying AI to this field.

Data-Driven Manufacturing: AI, ML, and Data Science

The innovation, community, and agility of open source software are unmatched, but Python ecosystems are not without risk. Security vulnerabilities are a reality in open-source code just as they are with proprietary software. It's a high-stakes game that depends on the robustness of your supply chain security. Scanning for security vulnerabilities is not enough; you must trust where your open-source software packages, libraries, and databases originate. We’re here to help.


In this webinar, you will learn:

Where, why, and how security issues might creep into your Python and R open-source ecosystem
How a single compromised open-source component can lead to a cascade of security breaches
Key steps for securing your open-source supply chain and a roadmap of risks you can reference with your teams to build security awareness

How to Secure Your Python Open-Source Supply Chain from Hidden Threats

As the adoption of artificial intelligence, machine learning, and data science (AI/ML/DS) continues to grow, the importance of open source security has never been more critical.

Today, upwards of 95% of enterprises rely on open source for rapid innovation making them attractive targets for threat actors who may attempt to compromise popular packages or distribute malicious ones.

Join Anaconda’s Principal Solutions Architect, Frank Yang, to learn how to secure your open source supply chain. This session will:

Delve into the challenges and risks associated with open-source

Demystify software supply chain security

Share best practices for mitigating open source risks

You will gain key insights on how to assess and secure your software supply chain and leverage open source innovations safely in your enterprise.

Securing Your AI/ML & Data Science Supply Chain

Cybersecurity Awareness Month 2023 - Understanding the Open Source Landscape.

Enterprise use of open-source software (OSS) has seen continued growth in recent years, powering rapid innovation and solution development. Unfortunately, as OSS use has increased, so too have software supply chain attacks. In the battle against software supply chain risk, common vulnerabilities and exposures (CVEs) serve as critical tools. In this session, we'll dive into CVEs and how to handle them. Questions we'll cover include:

Where does CVE data come from?
What goes into a CVE score?
What are the benefits and limitations of public CVE data?
How can enterprises use CVEs to secure their OSS pipelines?

Know Your Enemy: Vulnerability Data And What To Do With It

Security

Security Awareness

software suppy chain

Python

Vulnerabilities

Data Breach

Data Management

Open Source

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Know Your Enemy: Vulnerability Data And What To Do With It

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Anaconda