This session explores Gemini's capabilities, architecture, and performance benchmarks. We'll delve into the significance of its extensive context window and address the critical aspects of safety, security, and responsible AI use. Hallucination, a common concern in LLM applications, remains a focal point of ongoing development. This talk will highlight recent advancements aimed at mitigating the risk of hallucination to enhance LLMs utility across various applications.

When was the last time you performed a mathematical operation on an email address? Or multiplied a credit card number by a passport number?

It's absurd, this would be an insane thing to do, yet we keep storing sensitive customer information in our data warehouses, risking PII exposure, as if we need to perform operations like this. This forces our data teams to act as data police, controlling access—a job that's the definition of “not fun” and quickly becomes unmanageable. Companies are then faced with the difficult choice of either locking down all access or granting over-privileged access, neither of which is ideal.

But what if there's a better way?

In this talk, we'll explore how leading tech companies with the largest amount of customer data solve this problem. We'll look at the architectural patterns they use to balance data security and usability, and how these solutions can free our data teams from their policing duties.

As organizations transition from digital to AI-native, data becomes the linchpin of innovation, empowering AI to turn raw information into actionable insights. Cloudera hybrid data platform brings all data to modern use cases including Generative AI. This session explores how Cloudera can help your organization deploy robust AI use cases to production faster, without compromising performance, accuracy, and security.

Discover how Natwest approaches governance, security and privacy controls as well as their roadmap for building a modern data architecture.

Join this session to discover how Natwest approaches governance, security & privacy controls, focusing on how they've designed & implemented a framework that balances control with agility. We will dive into NatWest's journey to establish a robust foundation for federated governance using a hub-and-spoke model. Attendees will gain insights into how NatWest enables a scalable governance structure that empowers individual teams while maintaining centralised oversight. Additionally, NatWest will share their roadmap for building a modern data architecture, guided by Data Mesh principles, that ensures flexibility, scalability, and alignment with the evolving needs of the organisation. This session is a must-attend for those looking to modernise their data strategies with a focus on governance and architectural innovation.

PrimaryBid is on a mission to improve the global IPO market by allowing frictionless participation to more investors than ever before. Central to achieving this mission is the ability to deliver real-time data analytics to a range of audiences. Join us as we discuss our journey to building a best-in-class embedded analytics solution. From dissecting what it means to be best-in-class in 2024, through to identifying constraints and choosing the right technology partners - we?ll provide a how-to, and how-not-to, on creating a premium analytics experience. In an industry where speed, aesthetics, reliability, security, and governance are paramount, discover how we optimize across all dimensions. The session includes a comprehensive overview of our progress to date and a live demonstration showcasing our product in action.

Big data has moved beyond being just a buzzword; it's now at the heart of modern business strategies. When used effectively and efficiently, data can open up new revenue opportunities, provide deep insights, and even drive social impact. As digital transformation accelerates, data is no longer just a tool—it's woven into the fabric of every part of an organization. Designing and maintaining a tier 1 data platform has become essential to staying ahead of the competition. 

Especially with AI-driven applications on the rise, the convergence of DevSecOps and DataOps is becoming increasingly critical. The recent global disruption caused by a security company's mistake was a wake-up call—highlighting just how high the stakes can be. Building and scaling data platforms isn't enough; security and scalability need to be integral to the entire data lifecycle. 

Bringing more than a decade of SRE experience to maintaining and managing top enterprise software, we will discuss how to tear down silos and encourage collaboration among development, security, operations, and data teams. By doing so, organizations can achieve unprecedented levels of reliability and security. Integrating DevSecOps with DataOps doesn't just automate and protect data operations—it also safeguards data integrity, privacy, and compliance, even as data environments expand in size and complexity. In today's competitive market, this proactive stance is what will set the leaders apart from the rest.

Main Actionable Takeaways:

• Cultivate a Collaborative Culture

• Prioritize Resilience and Recovery

• Integrate Security Seamlessly into Data Pipeline

How can the public sector thrive without data clarity and security?

Join Professor Vishnu Chandrabalan, Director and Chief Clinical Information Officer of the Lancashire and South Cumbria Secure Data Environment (SDE), as he shares his team’s journey towards securing NHS data to enable better research outcomes and patient care.

Improve your data infrastructure with governance and security, using proven methods and best practices. Break down data silos, foster collaboration, and optimise data accessibility, empowering your business units with the data and technologies they need. Learn how AI improves efficiency and streamlines data product development. And see how Microsoft Fabric simplifies data estate modernization with a focus on unifying your data in an open and governed foundation.

In this session, we will demo and discuss the four central pillars of an enterprise strategy to realize true ""Gen-BI"" - the infusion of Gen-AI and LLMs into your business and decision intelligence capabilities.

        • Direct operations on any data source, accessible to any user 

        • Sophisticated request handling through the simplicity of conversational speech 

        • The 'Multi-LLM' strategy - to bring the right model for the right data set

        • Security so you can tap into Gen-AI without concern

Condé Nast is one of the world's most renowned media companies that creates and distributes content with a footprint of over 1 billion consumers in 32 territories through print, digital, video, and social platforms. At the heart of Condé Nast is data to better understand and delight our customers. The company’s data governance experts play a critical role in maintaining the highest quality of content and ensuring data integrity, security, and accessibility while optimizing consumer engagement. Condé Nast's data culture promotes and measures data governance alongside data search and discovery, enables data leadership, and focuses strongly on data literacy to maximize return on investment for data programs. Learn from data governance expert, Hilda Sadek, on what it takes to build a transformative, high-growth data culture using data governance.

As organizations transition from digital to AI-native, data becomes the linchpin of innovation, empowering AI to turn raw information into actionable insights. Cloudera hybrid data platform brings all data to modern use cases including Generative AI. This session explores how Cloudera can help your organization deploy robust AI use cases to production faster, without compromising performance, accuracy, and security.

This talk will explore a platform strategy that emphasizes the decentralization of data and analytics, aiming to achieve an optimal balance between autonomy and governance, thereby increasing iteration and innovation speed while ensuring compliance with regulations. Attendees will learn how to support the entire data product lifecycle, enabling teams to operate independently while adhering to governance and architectural standards. 

The discussion will highlight the following key areas:

1. Autonomy and Innovation: How decentralized data platforms empower teams to innovate faster by reducing dependencies and bottlenecks. Examples of successful implementations will be provided, illustrating how autonomy can lead to increased iteration and innovation speed.

2. Governance and Compliance: Strategies for maintaining robust governance frameworks that ensure data quality, security, and compliance with regulations such as GDPR and HIPAA. The talk will cover tools and best practices for monitoring and enforcing compliance in a decentralized environment.

3. Data Product lifecycle: A comprehensive approach to supporting the data product lifecycle, from data product prototyping to the data product operations, monitoring and change management. 

4. Adoption: Real-world scenarios where organizations have navigated the trade-offs between autonomy and governance, creating the right condition for platform adoption.

Like many large businesses Maersk relies on a centrally managed Data Lake to deliver customer insights and business reports. But in today's fast-paced business environment, timely and accurate decision-making relies heavily on the ability to access and analyse data at will. Opening up your Data Lake and allowing business users the ability to query the data directly, could bring major benefits; but also brings with it technical and security challenges. 

Join Graham and Julian as they explore how Maersk has used Dremio software to deliver Self Service Analytics and their checklist of the essential ‘must have’ technical capabilities.

In today’s episode, I’m going to perhaps work myself out of some consulting engagements, but hey, that’s ok! True consulting is about service—not PPT decks with strategies and tiers of people attached to rate cards. Specifically today, I decided to reframe a topic and approach it from the opposite/negative side. So, instead of telling you when the right time is to get UX design help for your enterprise SAAS analytics or AI product(s), today I’m going to tell you when you should NOT get help! 

Reframing this was really fun and made me think a lot as I recorded the episode. Some of these reasons aren’t necessarily representative of what I believe, but rather what I’ve heard from clients and prospects over 25 years—what they believe. For each of these, I’m also giving a counterargument, so hopefully, you get both sides of the coin. 

Finally, analytical thinkers, especially data product managers it seems, often want to quantify all forms of value they produce in hard monetary units—and so in this episode, I’m also going to talk about other forms of value that products can create that are worth paying for—and how mushy things like “feelings” might just come into play ;-)  Ready?

Highlights/ Skip to:

(1:52) Going for short, easy wins (4:29) When you think you have good design sense/taste  (7:09) The impending changes coming with GenAI (11:27) Concerns about "dumbing down" or oversimplifying technical analytics solutions that need to be powerful and flexible (15:36) Agile and process FTW? (18:59) UX design for and with platform products (21:14) The risk of involving designers who don’t understand data, analytics, AI, or your complex domain considerations  (30:09) Designing after the ML models have been trained—and it’s too late to go back  (34:59) Not tapping professional design help when your user base is small , and you have routine access and exposure to them   (40:01) Explaining the value of UX design investments to your stakeholders when you don’t 100% control the budget or decisions 

Quotes from Today’s Episode “It is true that most impactful design often creates more product and engineering work because humans are messy. While there sometimes are these magic, small GUI-type changes that have big impact downstream, the big picture value of UX can be lost if you’re simply assigning low-level GUI improvement tasks and hoping to see a big product win. It always comes back to the game you’re playing inside your team: are you working to produce UX and business outcomes or shipping outputs on time? ” (3:18) “If you’re building something that needs to generate revenue, there has to be a sense of trust and belief in the solution. We’ve all seen the challenges of this with LLMs. [when] you’re unable to get it to respond in a way that makes you feel confident that it understood the query to begin with. And then you start to have all these questions about, ‘Is the answer not in there,’ or ‘Am I not prompting it correctly?’ If you think that most of this is just an technical data science problem, then don’t bother to invest in UX design work… ” (9:52) “Design is about, at a minimum, making it useful and usable, if not delightful. In order to do that, we need to understand the people that are going to use it. What would an improvement to this person’s life look like? Simplifying and dumbing things down is not always the answer. There are tools and solutions that need to be complex, flexible, and/or provide a lot of power – especially in an enterprise context. Working with a designer who solely insists on simplifying everything at all costs regardless of your stated business outcome goals is a red flag—and a reason not to invest in UX design—at least with them!“ (12:28)“I think what an analytics product manager [or] an AI product manager needs to accept is there are other ways to measure the value of UX design’s contribution to your product and to your organization. Let’s say that you have a mission-critical internal data product, it’s used by the most senior executives in the organization, and you and your team made their day, or their month, or their quarter. You saved their job. You made them feel like a hero. What is the value  of giving them that experience and making them feel like those things… What is that worth when a key customer or colleague feels like you have their back with this solution you created? Ideas that spread, win, and if these people are spreading your idea, your product, or your solution… there’s a lot of value in that.” (43:33)

“Let’s think about value in non-financial terms. Terms like feelings. We buy insurance all the time. We’re spending money on something that most likely will have zero economic value this year because we’re actually trying not to have to file claims. Yet this industry does very well because the feeling of security matters. That feeling is worth something to a lot of people. The value of feeling secure is something greater than whatever the cost of the insurance plan. If your solution can build feelings of confidence and security, what is that worth? Does “hard to measure precisely” necessarily mean “low value?”  (47:26)

Webinar on how Blockchain meets security needs. Speaker: Joshua Blanchard, CTO of Blackwallet Ltd. Hosted by Government Blockchain Association. Time: Thursday at noon EDT.

From Tableau Conference 2024, watch this recording of one of the popular Hands-on Training Sessions.

Swipe Right on Virtual Connections Fall in love with Tableau all over again when you learn how virtual connections can help you scalably govern connectivity, manage data access policies, and centralize row-level security.

Using API keys? Then listen up! Many times API keys is the easy choice but they also constitute a risk. Learn how to mitigate this risk by using managed identity on Azure. But what even is managed identity? Let's explain this new concept and look at a practical example.