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| Title & Speakers | Event |
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Richie
– host
@ DataCamp
,
Colin Zima
– CEO
@ Omni
The modern data stack has transformed how organizations work with data, but are our BI tools keeping pace with these changes? As data schemas become increasingly fluid and analysis needs range from quick explorations to production-grade reporting, traditional approaches are being challenged. How can we create analytics experiences that accommodate both casual spreadsheet users and technical data modelers? With semantic layers becoming crucial for AI integration and data governance growing in importance, what skills do today's BI professionals need to master? Finding the balance between flexibility and governance is perhaps the greatest challenge facing data teams today. Colin Zima is the Co-Founder and CEO of Omni, a business intelligence platform focused on making data more accessible and useful for teams of all sizes. Prior to Omni, he was Chief Analytics Officer and VP of Product at Looker, where he helped shape the product and data strategy leading up to its acquisition by Google for $2.6 billion. Colin’s background spans roles in data science, analytics, and product leadership, including positions at Google, HotelTonight, and as founder of the restaurant analytics startup PrimaTable. He holds a degree in Operations Research and Financial Engineering from Princeton University and began his career as a Structured Credit Analyst at UBS. In the episode, Richie and Colin explore the evolution of BI tools, the challenges of integrating casual and rigorous data analysis, the role of semantic layers, and the impact of AI on business intelligence. They discuss the importance of understanding business needs, creating user-focused dashboards, and the future of data products, and much more. Links Mentioned in the Show: OmniConnect with ColinSkill Track: Design in Power BIRelated Episode: Self-Service Business Intelligence with Sameer Al-Sakran, CEO at MetabaseRegister for RADAR AI - June 26 New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business |
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#264 From Gen AI to Gen BI with Omri Kohl, CEO and Co-Founder of Pyramid Analytics
2024-11-25 · 10:00
We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here. The convergence of AI and business intelligence is creating new opportunities for innovation. As AI becomes more embedded in BI tools, the challenge lies in fostering a data-driven culture within organizations. How can professionals bridge the gap between intuition and data-driven decision-making? What strategies can be employed to cultivate a culture where data is at the forefront of business decisions? And how can AI tools be leveraged to make data insights more accessible to all employees? Omri Kohl is the CEO and co-founder of Pyramid Analytics, the Trusted Analytics Platform built for the enterprise. He leads Pyramid’s strategy and operations through a fast-growing data and analytics market. Kohl brings a deep understanding of analytics and AI technologies, valuable management experience, and a natural ability to challenge conventional thinking. Since Kohl founded Pyramid in 2009, it has achieved significant market success and customer growth. Kohl is a highly experienced entrepreneur with a proven track record developing and managing fast-growth companies. In the episode, Richie and Omri explore the evolution of BI with AI, the importance of data-driven culture, the role of generative BI in democratizing insights, the balance between intuition and data, and much more. Links Mentioned in the Show: Pyramid AnalyticsConnect with OmriPyramid Analytics GenBI DemoCourse: Introduction to Data CultureRelated Episode: Self-Service Business Intelligence with Sameer Al-Sakran, CEO at MetabaseRewatch sessions from RADAR: Forward Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business |
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Sameer Al-Sakran
– CEO
@ Metabase
,
Richie
– host
@ DataCamp
We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here. We’re often caught chasing the dream of “self-serve” data—a place where data empowers stakeholders to answer their questions without a data expert at every turn. But what does it take to reach that point? How do you shape tools that empower teams to explore and act on data without the usual bottlenecks? And with the growing presence of natural language tools and AI, is true self-service within reach, or is there still more to the journey? Sameer Al-Sakran is the CEO at Metabase, a low-code self-service analytics company. Sameer has a background in both data science and data engineering so he's got a practitioner's perspective as well as executive insight. Previously, he was CTO at Expa and Blackjet, and the founder of SimpleHadoop and Adopilot. In the episode, Richie and Sameer explore self-serve analytics, the evolution of data tools, GenAI vs AI agents, semantic layers, the challenges of implementing self-serve analytics, the problem with data-driven culture, encouraging efficiency in data teams, the parallels between UX and data projects, exciting trends in analytics, and much more. Links Mentioned in the Show: MetabaseConnect with SameerArticles from Metabase on jargon, information budgets, analytics mistakes, and data model mistakesCourse: Introduction to Data CultureRelated Episode: Towards Self-Service Data Engineering with Taylor Brown, Co-Founder and COO at FivetranRewatch Sessions from RADAR: Forward Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business |
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Sameer Al-Sakran
– CEO
@ Metabase
,
Tobias Macey
– host
Summary Business Intelligence software is often cumbersome and requires specialized knowledge of the tools and data to be able to ask and answer questions about the state of the organization. Metabase is a tool built with the goal of making the act of discovering information and asking questions of an organizations data easy and self-service for non-technical users. In this episode the CEO of Metabase, Sameer Al-Sakran, discusses how and why the project got started, the ways that it can be used to build and share useful reports, some of the useful features planned for future releases, and how to get it set up to start using it in your environment. Preamble Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline you’ll need somewhere to deploy it, so check out Linode. With private networking, shared block storage, node balancers, and a 40Gbit network, all controlled by a brand new API you’ve got everything you need to run a bullet-proof data platform. Go to dataengineeringpodcast.com/linode to get a $20 credit and launch a new server in under a minute. For complete visibility into the health of your pipeline, including deployment tracking, and powerful alerting driven by machine-learning, DataDog has got you covered. With their monitoring, metrics, and log collection agent, including extensive integrations and distributed tracing, you’ll have everything you need to find and fix performance bottlenecks in no time. Go to dataengineeringpodcast.com/datadog today to start your free 14 day trial and get a sweet new T-Shirt. Go to dataengineeringpodcast.com to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch. Your host is Tobias Macey and today I’m interviewing Sameer Al-Sakran about Metabase, a free and open source tool for self service business intelligence Interview Introduction How did you get involved in the area of data management? The current goal for most companies is to be “data driven”. How would you define that concept? How does Metabase assist in that endeavor? What is the ratio of users that take advantage of the GUI query builder as opposed to writing raw SQL? What level of complexity is possible with the query builder? What have you found to be the typical use cases for Metabase in the context of an organization? How do you manage scaling for large or complex queries? What was the motivation for using Clojure as the language for implementing Metabase? What is involved in adding support for a new data source? What are the differentiating features of Metabase that would lead someone to choose it for their organization? What have been the most challenging aspects of building and growing Metabase, both from a technical and business perspective? What do you have planned for the future of Metabase? Contact Info Sameer salsakran on GitHub @sameer_alsakran on Twitter LinkedIn Metabase Website @metabase on Twitter metabase on GitHub Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Links Expa Metabase Blackjet Hadoop Imeem Maslow’s Hierarchy of Data Needs 2 Sided Marketplace Honeycomb Interview Excel Tableau Go-JEK Clojure React Python Scala JVM Redash How To Lie With Data Stripe Braintree Payments The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA Support Data Engineering Podcast |
Data Engineering Podcast |