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The Road to Intelligent Data Apps

with Shelly Kramer and George Gilbert

About the podcast

The Road to Intelligent Data Apps, theCUBE Research analysts Shelly Kramer and George Gilbert explore why intelligent data apps are the next frontier. As we move beyond the last decade in data and analytics, which was all about cloud architecture and separating compute from storage, and into the next decade, which is all about separating compute from data, we’ve evolving into a whole new system of truth.

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The Road to Intelligent Data Apps

In this new video series: The Road to Intelligent Data Apps, theCUBE Research analysts Shelly Kramer and George Gilbert explore why intelligent data apps are the next frontier.

As we move beyond the last decade in data and analytics, which was all about cloud architecture and separating compute from storage, and into the next decade, which is all about separating compute from data, we've evolving into a whole new system of truth.

Find out more about theCUBE’s coverage of AWS re:Invent https://events.cube365.net/supercloud/aws-reinvent-2023-cube-coverage

This series explores the opportunities and challenges ahead, with a preview of AWS re:Invent 2023, along with thoughts on some current players in this arena.

Follow theCUBE's wall-to-wall coverage as the roving news desk for SiliconANGLE reports live from tech's top events
https://siliconangle.com/category/cube-event-coverage/

Catch up on the most recent episode of the AnalystANGLE https://www.youtube.com/playlist?list=PLenh213llmcYnzc3JScBR0fSUUWbHh1EH

YouTube Video UExlbmgyMTNsbG1jWnFDNDk3UUV0b3p4MEJVbGRLUXBiZC41NkI0NEY2RDEwNTU3Q0M2

Shelly Kramer & George Gilbert | The Road to Intelligent Data Apps

7.9K views

This is theCUBE's latest episode in our series, The Road to Intelligent Data Apps, which focuses on the evolution of the modern data stack into the new platform for applications, or what we’re calling “the sixth data platform.” This modern data stack is becoming the new platform for applications as raw cloud infrastructure recedes into the background. In this series, we feature insights from some of the brightest minds in the tech world.

For this episode, theCUBE Research principal analyst Shelly Kramer welcomes Bob Muglia, who pretty much needs no introduction, certainly within the tech industry.

Check out the latest from theCUBE, including upcoming tech events https://www.thecube.net/

Bob was president of the precursor to Microsoft’s Enterprise Division, growing it to $14 billion in revenue. Most recently, Bob was CEO of Snowflake, leading it from $0 revenue and guiding the company to an IPO, which was the largest ever debut of an enterprise software company. Today, Bob is an investor, advisor and mentor to some of the most exciting companies driving the evolution of the modern data stack. Bob is also the author of The Datapreneurs, which focuses on the promise of AI and the creators who are building our future.

Follow theCUBE's wall-to-wall coverage as the roving news desk for SiliconANGLE reports live from tech's top events https://siliconangle.com/category/cube-event-coverage/

Our conversation explored what’s involved in building a modern data platform, as well as a deep dive into the five major data platforms in use today: Databricks, Snowflake, Microsoft, Google, and AWS, comparing and contrasting their capabilities, market differentiators and challenges they face.

Keep up to date on the latest from “The Road to Intelligent Data Apps” series https://www.youtube.com/playlist?list=PLenh213llmcZqC497QEtozx0BUldKQpbd

We also explored the role we expect generative AI to play in accelerating all aspects of application development (e.g. for modeling data and the business), as well as a discussion around the role of Relational Knowledge Graph in reimagining data and apps.

As expected, Bob had great insights to share and the conversation is truly the ultimate insider’s guide to the future of the modern data stack.

#dataapps #intelligentdataapps #Snowflake #Databricks #Microsoft #Google #AWS, #generativeAI #theCUBEResearch #TheDatapreneurs #dataplatform #moderndataplatform #relationalknowledgegraph #applicationdevelopment #applications #applicationplatforms #creators #creatoreconomy #artificialintelligence #AI

YouTube Video UExlbmgyMTNsbG1jWnFDNDk3UUV0b3p4MEJVbGRLUXBiZC4yODlGNEE0NkRGMEEzMEQy

The Ultimate Insider’s Guide to the Modern Data Stack with Bob Muglia

9.1K views

In this episode of The Road to Intelligent Data Apps, theCUBE Research analysts Shelly Kramer and George Gilbert are joined by Rahul Auradkar, EVP and GM, Salesforce Data Cloud and Einstein Platform, for a discussion centered on intelligent data apps and the transition that is underway as organizations work to shift the way data is managed and upleveled throughout an organization.

Check out the latest from theCUBE, including upcoming tech events https://www.thecube.net/

Auradkar shared insights on Salesforce Data Cloud, the vision behind what Salesforce is doing, and the impetus and genesis of Data Cloud, along with thoughts on the set up needed for the metadata-driven approach. This includes embedding and integrating all data so that there is an enterprise-wide view of the status of an enterprise, and then shifting that view from strings to things by capturing all the intelligence that has traditionally been siloed in operational apps.

Follow theCUBE's wall-to-wall coverage as the roving news desk for SiliconANGLE reports live from tech's top events https://siliconangle.com/category/cube-event-coverage/

Intelligent data apps can call on all the "things" and each other to engage with people and customers through insights and automation. But this doesn't come without challenges; including the reality that putting intelligence into "things" requires metadata, which must be standardized and shared throughout the organization.

Keep up to date on the latest from “The Road to Intelligent Data Apps” series https://www.youtube.com/playlist?list=PLenh213llmcZqC497QEtozx0BUldKQpbd

#intelligentdata #Salesforce #theCUBEResearch #DataCloud #metadata #enterpriseapps #intelligentdataapps
#SalesforceDataCloud #vectordbsearch #einsteincopilot #analytics #dataanalytics #datamanagement

YouTube Video UExlbmgyMTNsbG1jWnFDNDk3UUV0b3p4MEJVbGRLUXBiZC4wMTcyMDhGQUE4NTIzM0Y5

Salesforce Data Cloud uplevels the modern data stack | The Road to Intelligent Data Apps

8.1K views

Welcome to this episode of The Road to Intelligent Data Apps, a video podcast delving into the future of data. Hosted by Dave Vallante, chief analyst, alongside George Gilbert, senior analyst, both with theCUBE Research. Today's guest is Soma Somasegar, managing director at Madrona Venture Group. A seasoned professional, he joined Madrona Ventures in 2015, specializing in B2B and Enterprise startups following a successful 27-year tenure at Microsoft, where he served as VP of the developer division.

Check out the latest from theCUBE, including upcoming tech events https://www.thecube.net/

The discussion revisits Madrona's Intelligent Application Summit, exploring the concept of intelligent apps and their significance. Somasegar highlights the evolution of AI investments over the past decade, emphasizing the transformative potential of intelligent applications. From the data explosion to continuous learning systems, the conversation underscores the pivotal role of AI in reshaping enterprise apps and the modern data stack. Additionally, there's a glimpse into the future of AI-driven ERP and CRM solutions, signaling a shift towards innovation in established markets.

Follow theCUBE's wall-to-wall coverage as the roving news desk for SiliconANGLE reports live from tech's top events https://siliconangle.com/category/cube-event-coverage/

Keep up to date on the latest from “The Road to Intelligent Data Apps” series https://www.youtube.com/playlist?list=PLenh213llmcZqC497QEtozx0BUldKQpbd

#TheRoadtoIntelligentDataApps #theCUBE #theCUBEResearch #MadronaVentures #IntelligentApplicationSummit #AI #ERP #CRM

YouTube Video UExlbmgyMTNsbG1jWnFDNDk3UUV0b3p4MEJVbGRLUXBiZC41MjE1MkI0OTQ2QzJGNzNG

Madrona Ventures' Soma Somasegar | Road to Intelligent Data Apps

2.1K views

In this episode of The Road to Intelligent Data Apps, Shelly Kramer, managing director and principal analyst at theCUBE Research is joined by analyst George Gilbert and Jason Pohl, Senior Director of Data Management for Databricks

This is part of our continuing conversation about the Sixth Data Platform, an emerging data platform where the leading vendors are Databricks, Snowflake, AWS, Azure, and Google. If you're new to this conversation, what we’re seeing in this evolution is that the data platform is actually becoming an application platform, as all applications are becoming driven by data, analytics, and AI.

For our discussion today, we take a closer look at Databricks; both the company roadmap and the customer activity, and we’re thrilled to have Jason join us.

First, some historical context: Snowflake defined the modern data stack with the separation of compute from storage, which essentially allowed the management of infinite amounts of data in a data lakehouse architecture.

The data lakehouse gave customers a simple solution for managing their end-to-end data analytic data estate.

And here’s where it gets interesting: We see Databricks redefining Snowflake's core innovation of separating storage from compute and that's part of the reason we were excited about this conversation with Jason. Our discussion covered a variety of things, including:

- An overview of the Databricks' version of the data lakehouse, in which storage and compute can come from different vendors.

- The process by which end-to-end data management shifts to end-to-end data governance in the Databricks Unity catalog

- A key differentiator for Databricks is that different compute engines, including Snowflake, can run different workloads on the data, providing customers with a much wider price, choice and performance or capabilities.

- An exploration of what a data lakehouse is and how it differs from a more traditional data platform (e.g., multi-vendor compute versus single vendor, governance separate from DMBS, etc.), as well as what the ability to write data in open format for multiple engines means for customers.

- An overview of how Databricks' Intelligent Lakehouse solution works and how that benefits customers.

We discussed workloads and what distinguishes them and explored where customers are in deployment and production of their AI workloads, along with how customers can leverage the tools and pipelines in traditional ML workloads in building their Gen AI functionality.

Other topics covered include:

- Application platforms and how we expect the definition of apps will change over time. How this impacts how devs build apps and operationalize analytics, and the role of workflow and transaction support.

- There was much discussion around data governance and its key role, as well as multi-vendor data estates and how and when customers are using compute engines from multiple vendors.

- Databricks' Unity Catalog and the growth capabilities they envision there over time, as well as how customers plan to implement Unity.

We wrapped the episode with a conversation about Databricks' vision for the Intelligent Lakehouse and what we collectively see ahead for the industry.

YouTube Video UExlbmgyMTNsbG1jWnFDNDk3UUV0b3p4MEJVbGRLUXBiZC4wOTA3OTZBNzVEMTUzOTMy

Databricks on Intelligent Data Apps | Road to Intelligent Data

1.4K views

00:00 - Exploring Innovation: The Journey and Architectural Insights of Madan Thangavelu
04:15 - Core Entities in Uber's System
06:37 - Business Process Logic in Microservices
09:48 - Transaction Logic and App Development
14:55 - AI/ML in Real-time Context
24:13 - Uber Rider App Evolution
30:18 - Modular Architecture for Scalability
36:20 - Integrating Logic, Insights, and Future Perspectives

In this interview, Madan Thangavelu, senior engineering director for Uber's flagship Rider app, talks to theCUBE Research’s George Gilbert as he reflects on his decade-long journey at Uber and the app's evolution from a simple A-to-B travel platform to a multifaceted service offering package delivery, car rental and even train booking.

Check out the latest from theCUBE, including upcoming tech events https://www.thecube.net/

Thangavelu delves into the real-time nature of Uber's system, emphasizing the need for synchronization across layers and microservices to ensure up-to-date information for users and drivers alike. He also discusses the development of standardized APIs and libraries, enabling seamless interactions and transactions within the app's complex ecosystem.

Follow theCUBE's wall-to-wall coverage as the roving news desk for SiliconANGLE reports live from tech's top events https://siliconangle.com/category/cube-event-coverage/

Thangavelu explores the challenges of managing a real-time system at scale, highlighting the importance of anomaly detection and real-time metric monitoring to maintain system reliability. Ultimately, Thangavelu envisions leveraging large amounts of real-time data to create even more dynamic and personalized app experiences in the future.

Keep up to date on the latest from “The Road to Intelligent Data Apps” series https://www.youtube.com/playlist?list=PLenh213llmcZqC497QEtozx0BUldKQpbd

#TheRoadtoIntelligentDataApps #theCUBE #theCUBEResearch #Uber #synchronization #Apps

YouTube Video UExlbmgyMTNsbG1jWnFDNDk3UUV0b3p4MEJVbGRLUXBiZC41MzJCQjBCNDIyRkJDN0VD

Uber - Building the Flagship Rider App | The Road to intelligent Data Apps

4.1K views

George Gilbert, senior analyst at theCUBE Research, talks with Param Kahlon, EVP and GM at Salesforce, about the integral components of Salesforce's innovative framework, particularly focusing on the triad of the AI platform, the data Cloud platform and integration automation.

Check out the latest from theCUBE, including upcoming tech events https://www.thecube.net/

AI is a necessary component in today’s applications, Kahlon says, as he highlights Salesforce's long-standing expertise in predictive and generative AI. The data Cloud platform is pivotal in grounding AI predictions with relevant contextual data, addressing the challenge of disparate data across enterprises. Integration automation emerges as the solution to seamlessly consolidate data and enable AI-driven insights and real-time actions.

Follow theCUBE's wall-to-wall coverage as the roving news desk for SiliconANGLE reports live from tech's top events https://siliconangle.com/category/cube-event-coverage/

These components work together to drive digital and AI-led transformations, according to Kahlon. He illustrates this synergy by giving examples of businesses streamlining processes and enhancing customer experiences. The conversation also touches on the future potential of autonomous agents and advanced automation, suggesting a promising trajectory for Salesforce's evolution.

Keep up to date on the latest from “The Road to Intelligent Data Apps” series https://www.youtube.com/playlist?list=PLenh213llmcZqC497QEtozx0BUldKQpbd

#TheRoadtoIntelligentDataApps #theCUBE #Salesforce #theCUBEResearch #GenerativeAI #DigitalTransformation #automation

YouTube Video UExlbmgyMTNsbG1jWnFDNDk3UUV0b3p4MEJVbGRLUXBiZC5DQUNERDQ2NkIzRUQxNTY1

Salesforce - From Data Cloud to Agents | The Road to Intelligent Data Apps

3.7K views

In the latest episode of The Road to Intelligent Data Apps series, theCUBE Research analyst George Gilbert is joined by Dain Sundstrom, CTO of Starburst Data, and Ryan Blue, CEO of Tabular and creator of Iceberg. They explore the evolution and significance of separating storage from compute in modern data stacks.

Check out the latest from theCUBE, including upcoming tech events https://www.thecube.net/

This separation has allowed for scalable, cost-effective computing and improved interaction with various systems. The recent trend of enabling any compute engine to interact with common data foundations has transformed the data platform landscape and highlights the quick adoption by cloud providers, according to Blue.

Follow theCUBE's wall-to-wall coverage as the roving news desk for SiliconANGLE reports live from tech's top events https://siliconangle.com/category/cube-event-coverage/

There are ongoing challenges, such as achieving full compatibility across different data formats and ensuring consistent access controls and governance. Projects such as Iceberg are helping to create a universal data layer that supports broad industry collaboration and innovation, according to Blue.

Visit theCUBE Research for the latest in tech news https://thecuberesearch.com/

Catch up on all episode of The Road to Intelligent Data Apps series https://www.youtube.com/playlist?list=PLenh213llmcZqC497QEtozx0BUldKQpbd

#theCUBE #TheRoadToIntelligentDataApps #theCUBEResearch #DataStorage #Iceberg #scalability

YouTube Video UExlbmgyMTNsbG1jWnFDNDk3UUV0b3p4MEJVbGRLUXBiZC45NDk1REZENzhEMzU5MDQz

The Path to the Multi-Vendor Data Platform | The Road To Intelligent Data Apps

2.4K views

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