Name: Seeing the Forest and the Trees: Data Discovery in Billion Row datasets
Start: 2022-03-22T18:00:00Z
End: 2022-03-22T18:00:47.000Z
Location: BrightTALK
Rating: 5

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

Future Tech's Dan Chaney, VP of enterprise AI and data science solutions, speaks with AI industry experts about how organizations and universities are seeking to educate, recruit, and retain tomorrow's AI leaders.

Accelerating AI & Data Science: Future Tech is at the forefront of enterprise AI & Data Science solutions. We help companied accelerate their use of advance AI & Data Science solutions. Our customized data science workstations can reduce end-to-end data science workflows by up to 80%, helping your team to work smarter, faster and safer. Ask how we can create you the right customized data science workstation stack.

Winning the War for AI Talent

Bringing a Data Science program into large, entrenched companies poses significant challenges on two fronts: First, Enterprises' internal processes, organizational structure and culture pose a barrier to building a successful Data Science program. Second, data science and machine learning come with their own intrinsic challenges. Some problems take longer to solve than others. Furthermore, not all problems are solvable by data science. The speakers share their experience and views on both the Internal and Intrinsic challenges of establishing Data Science as a Core function within Enterprises.

The Essentials to Data Science Success within Enterprises

We are witnessing ever increasing innate human desire to gain insight in every industry and every walk of life. Our professional and personal lives are reliant on data and frictionless data technology to make sense of the insight to achieve significant outcomes. This insatiable human demand can only be fulfilled provided data and frictionless technologies are enabled with free and open approach.

Join me and industry leaders to explore industry trends to democratise data for humans to thrive in a digital data economy, we will discuss:

• What are significant challenges corporate humans (I.e., employees) face?
• Why should they care about this?
• What impact it has on their customers and their company’s success?
• Can AI/ML models ever make these humans effective in a closed data ecosystem?

Debarshi Bandyopadhyay, Principal Consultant & Delivery Partner, Infosys UK Limited
Hari Yedoti, Group Head of Data, Liquid Telecom

The Human Data Democracy

Today, big data has the potential to transform functions, industries, organizations, and governments with an unprecedented impact. Complacency is not an option. You may be asking, “Where are the opportunities?”, “How can we drive business value using data visualization with bottom-line impact?” Join me as we explore these questions and more.

Leveraging Big Data Analytics & Visualization for transformational growth

Automatically detect data issues and understand their root cause before anyone else.  If this sounds like it could save you hours (or days) spent on tracking down data issues and the reason they’re occurring, see how Anomalo can begin automatically monitoring your data for quality issues within minutes. We’ll be looking at simple, fast, and intelligent visualizations of anomalies automatically detected in your data.

Using automated visualizations to ensure confidence in your data

With data quickly evolving into an organizations most vital asset, it has become increasingly important to invest in visualization tools that help generate insights. Companies such as Tableau, Power BI, and Looker have made it easy to create visuals and share information across an organization, but just creating a visual isn’t always enough. There must be a compelling narrative, anchored by facts, to facilitate the communication that ultimately drives decision making. In this session, you will learn the science behind the message your visuals give off and how you can create more engaging visuals for your audience.

The Art of Storytelling through Engaging Visuals

Data monetization is used for realizing a type of competitive capability for organizations. It provides organizations with flexibility for using information assets in response to customer expectations and marketplace exposure.
Traditionally, Business Intelligence and Data Visualization were used only for descriptive analytics on internal data assets. In the recent times, there is increasing adopt of visual analytics in data monetization initiatives. Building a self-serve B2B Embedded Analytics Portal to productize the data offering from an organization.

Summarizing the benefits:
· Analytics application for data monetization strengths the business value of the product
· Improved data exploration and data analysis for a data product
· Consumption of greater volumes of data in less time, which improves operational efficiency
· Early detection of otherwise overlooked trends, outliers, and correlations between data assets, which may result in a competitive edge

Building Commercial Products using BI and Visual Analytics

With cloud permeating everywhere, it has become imperative for all Telco companies to adopt and migrate their data to cloud for all analytic workloads.
How has this effected BI workloads? Do cloud based BI solutions help Telcos?
Does Analytics in cloud deliver simpler path to predictive models? Uniform and standardized workloads?
Does it help in reducing implementation time, better data availability? And scalability of models?
A user’s perspective in Telco

Data Fabric for Analytics & Cloud : A Telco Realty

Businesses today are collecting ever increasing amounts of data but are not extracting its full value. Many professionals struggle with problematic data structures, capability shortfalls and a lack of strategy. 

Join L.E.K. to learn how to make the most of the intelligence at your fingertips to improve your profitability and stay ahead of the competition.

The webinar will be interactive with plenty of opportunities to ask your own burning data questions and learn from peers across range of businesses like yours.

What will you learn?

• How to maximise the potential of the data you already have
• What are the right data strategies and structures to adopt
• How to use data to build commercial advantage

Who should attend?

• Senior leaders across all industries who want to extract value from data
• Strategy heads who want to embrace data-driven decision making
• Finance and Commercial Directors searching for performance improvement
• M&A and Business Development professionals qualifying opportunities
• Transformation teams hungry for data that can fuel change

How to Unlock the Value of Data in Your Business

Data teams and developers continue to serve as the lynchpin for data-centric businesses. As these personas increasingly collaborate, they enable organizations to overcome shortcomings associated with using growing data sets to gain insight. Improving data analytics for real-time business intelligence (BI) and customer insight ranks as one of the business priorities driving the most significant technology spending. In this keynote session, learn how business leaders are modernizing their approach to BI to gain data intelligence faster.

Modernizing Business Intelligence Creates Path to Data Leadership

Data Visualization & Analytics for Business Intelligence

Let’s face it. For all the incredible innovations in modern BI, we still face limitations when it comes to live connections to large enterprise sources. Starburst provides the single point of live access to all enterprise data, wherever it resides, through Trino’s ANSI-SQL MPP engine. With big data access, and used in combination with ThoughtSpot, users can query and analyze billions of rows of data across many sources at speeds thought unimaginable. Starburst and ThoughtSpot give business analysts the tools to ask new questions with easy expanded access to new data sources.

This session with Tom Nats, Director of Customer Solutions at Starburst, along with Sean Zinsmeister, VP of Product Marketing at ThoughtSpot will share how ThoughtSpot, used in conjunction with Starburst, opens new avenues by incorporating new data sources and performing high-speed queries at scale.

Bringing Big Data to Enterprise BI with Starburst & ThoughtSpot

The global big data and business analytics market was valued at 168.8 billion U.S. dollars in 2018 and is forecast to grow to 274.3 billion U.S. dollars by 2022, according to Statista.  As there's more data being made available on nearly anything in the world, so is the number of ways businesses can leverage that data. Big data management solutions and technologies are evolving to give companies the best data-driven analytics and predictive insights with unparalleled accuracy.  While there are endless possibilities in what can be done with big data, companies need to know not only how to organize their data but leverage it to get the most out of it.  

Join this panel to stay up to date with what you need to know to plan for 2022 and learn:  

-What trends to look out for in 2022 
-How to sort through and leverage big data to get quality data-driven insights 
-How to use common Big Data technologies 
-How to keep your company up and track real-time data

Panelists:
Pragyansmita Nayak, Ph.D., Chief Data Scientist at Hitachi Vantara Federal
Sandra Carrico, VP, Machine Learning at Sorcero
Sean Hearne, Director, Program Management Office at Fiserv

Trends in Big Data and Analytics in 2022

When exploring and visualizing large datasets, you are usually faced with a tough choice between sparsely sampling your data and aggregation. In this talk, we'll show how to use Anaconda technologies to show all of your data, revealing both trends and outliers, and letting you explore even the largest datasets interactively in a web browser.

We'll discuss:
- How Datashader can render your entire dataset faithfully in milliseconds or seconds, with both trends and outliers easily visible. 
- How pairing Datashader with the Python-based interactive tools Bokeh, Panel, and HoloViews lets you work interactively with your data, selecting individual datapoints and local groups for further inspection and exploration
- How to make sense of incoming datasets and make them actionable without getting distracted by tuning plotting parameters or missing out on important insights.

Seeing the Forest and the Trees: Data Discovery in Billion Row datasets

Big Data

Data Visualization

Data Management

Workload Consolidation

Data Insights

Big Data Management

Data Sets

Data Infrastructure

Data Science

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IT Service Management

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Cloud Computing

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Big Data and Data Management

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Seeing the Forest and the Trees: Data Discovery in Billion Row datasets

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Anaconda