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Address: 122 Fifth Avenue, 122 5th Ave, New York, NY 10011 Come join us for our first in-person event at the NEW Microsoft office on 5th avenue, Manhattan (not the Times Square location) to recap on Summit for those that were there and for those that were not able to make it! We have an awesome DUG session led by Peter Joeckel & Kati Hvidtfeldt both of who have been in the Microsoft Ecosystem for years! Session 1: Best practices for the Budgeting and Discovery stages in selecting an ERP & CRM Time: 12:45 pm - 2:00 pm Key Topics Covered:
Insights & Takeaways:
What is different about this session is if you can convince your bosses to take the full afternoon off to join us, we have a second session in the afternoon on The Ultimate Executives Guide for D365 Implementation. Session 2: The Ultimate Executives Guide for D365 Implementation. Time: 3:00 pm - 5:00 pm Key Topics Covered
Insights & Takeaways
You can attend just our Dynamics User Group session only or join us for both! Refreshments: We will have lunch served at our Dynamics User Group and a happy hour to follow the second session! |
Best practices for the Budgeting and Discovery stages in selecting an ERP & CRM
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The state of VC within software and AI startups – with Peter Walker
2025-08-06 · 17:15
Gergely Orosz
– host
,
Peter Walker
– Head of Insights
@ Carta
Brought to You By: • WorkOS — The modern identity platform for B2B SaaS. • Statsig — The unified platform for flags, analytics, experiments, and more. • Sonar — Code quality and code security for ALL code. — In this episode of The Pragmatic Engineer, I sit down with Peter Walker, Head of Insights at Carta, to break down how venture capital and startups themselves are changing. We go deep on the numbers: why fewer companies are getting funded despite record VC investment levels, how hiring has shifted dramatically since 2021, and why solo founders are on the rise even though most VCs still prefer teams. We also unpack the growing emphasis on ARR per FTE, what actually happens in bridge and down rounds, and why the time between fundraising rounds has stretched far beyond the old 18-month cycle. We cover what all this means for engineers: what to ask before joining a startup, how to interpret valuation trends, and what kind of advisor roles startups are actually looking for. If you work at a startup, are considering joining one, or just want a clearer picture of how venture-backed companies operate today, this episode is for you. — Timestamps (00:00) Intro (01:21) How venture capital works and the goal of VC-backed startups (03:10) Venture vs. non-venture backed businesses (05:59) Why venture-backed companies prioritize growth over profitability (09:46) A look at the current health of venture capital (13:19) The hiring slowdown at startups (16:00) ARR per FTE: The new metric VCs care about (21:50) Priced seed rounds vs. SAFEs (24:48) Why some founders are incentivized to raise at high valuations (29:31) What a bridge round is and why they can signal trouble (33:15) Down rounds and how optics can make or break startups (36:47) Why working at startups offers more ownership and learning (37:47) What the data shows about raising money in the summer (41:45) The length of time it takes to close a VC deal (44:29) How AI is reshaping startup formation, team size, and funding trends (48:11) Why VCs don’t like solo founders (50:06) How employee equity (ESOPs) work (53:50) Why acquisition payouts are often smaller than employees expect (55:06) Deep tech vs. software startups: (57:25) Startup advisors: What they do, how much equity they get (1:02:08) Why time between rounds is increasing and what that means (1:03:57) Why it’s getting harder to get from Seed to Series A (1:06:47) A case for quitting (sometimes) (1:11:40) How to evaluate a startup before joining as an engineer (1:13:22) The skills engineers need to thrive in a startup environment (1:16:04) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode: — See the transcript and other references from the episode at https://newsletter.pragmaticengineer.com/podcast — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected]. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe |
The Pragmatic Engineer |
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Global AI Bootcamp {Berlin} | In-person
2025-04-11 · 11:00
Global AI Bootcamp Berlin 2025For Community, By the CommunityJoin us for Global AI Bootcamp Berlin 2025, a dedicated space for Tech and AI enthusiasts, developers, and professionals to learn, share, and collaborate. This event is part of a global initiative bringing together AI experts and learners to explore the latest innovations, best practices, and real-world applications of Artificial Intelligence on Microsoft Azure. Event Details
Pre-recorded Keynote SessionHear from Scott Hanselman, Guido van Rossum, Jennifer Marsman, and Sarah Bird as they discuss AI’s impact on development, Python’s role, and the importance of ethical AI. In-person Closing KeynoteHear from Christian Heilmann, VP of DevRel at WeAreDevelopers, as he explores “Vibe coding, creativity, craft and professionalism – are we making ourselves redundant?” – a thought-provoking session on the evolving role of developers in the age of AI. Speakers & Sessions at Global AI Bootcamp Berlin 2025
What to Expect?
Agenda \| Event Schedule
(Agenda subject to updates.) Global AI BootcampThe Global AI Community connects over 60,000 AI enthusiasts worldwide, fostering learning, collaboration, and skill development. The Global AI Bootcamp is a free, community-driven event dedicated to exploring AI's transformative potential, with a focus on Azure AI and Copilots. Partners, Friends and Communities
Crew and Team
** Important Notice**Photos and videos will be taken during the event for community highlights and social media. If you prefer not to be photographed, please inform the organizers upon arrival. Register & Learn More📌 Claim your Digital Event Badge Code: MRLFHW 📌 Register for the event 📌 Meetup Event Page #GlobalAIBootcamp \| globalai.community |
Global AI Bootcamp {Berlin} | In-person
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Global AI Bootcamp {Berlin} | In-person
2025-04-11 · 11:00
Global AI Bootcamp Berlin 2025For Community, By the CommunityJoin us for Global AI Bootcamp Berlin 2025, a dedicated space for Tech and AI enthusiasts, developers, and professionals to learn, share, and collaborate. This event is part of a global initiative bringing together AI experts and learners to explore the latest innovations, best practices, and real-world applications of Artificial Intelligence on Microsoft Azure. Event Details
Pre-recorded Keynote SessionHear from Scott Hanselman, Guido van Rossum, Jennifer Marsman, and Sarah Bird as they discuss AI’s impact on development, Python’s role, and the importance of ethical AI. In-person Closing KeynoteHear from Christian Heilmann, VP of DevRel at WeAreDevelopers, as he explores “Vibe coding, creativity, craft and professionalism – are we making ourselves redundant?” – a thought-provoking session on the evolving role of developers in the age of AI. Speakers & Sessions at Global AI Bootcamp Berlin 2025
What to Expect?
Agenda \| Event Schedule
(Agenda subject to updates.) Global AI BootcampThe Global AI Community connects over 60,000 AI enthusiasts worldwide, fostering learning, collaboration, and skill development. The Global AI Bootcamp is a free, community-driven event dedicated to exploring AI's transformative potential, with a focus on Azure AI and Copilots. Partners, Friends and Communities
Crew and Team
** Important Notice**Photos and videos will be taken during the event for community highlights and social media. If you prefer not to be photographed, please inform the organizers upon arrival. Register & Learn More📌 Claim your Digital Event Badge Code: MRLFHW 📌 Register for the event 📌 Meetup Event Page #GlobalAIBootcamp \| globalai.community |
Global AI Bootcamp {Berlin} | In-person
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Global AI Bootcamp {Berlin} | In-person
2025-04-11 · 11:00
Global AI Bootcamp Berlin 2025For Community, By the CommunityJoin us for Global AI Bootcamp Berlin 2025, a dedicated space for Tech and AI enthusiasts, developers, and professionals to learn, share, and collaborate. This event is part of a global initiative bringing together AI experts and learners to explore the latest innovations, best practices, and real-world applications of Artificial Intelligence on Microsoft Azure. Event Details
Pre-recorded Keynote SessionHear from Scott Hanselman, Guido van Rossum, Jennifer Marsman, and Sarah Bird as they discuss AI’s impact on development, Python’s role, and the importance of ethical AI. In-person Closing KeynoteHear from Christian Heilmann, VP of DevRel at WeAreDevelopers, as he explores “Vibe coding, creativity, craft and professionalism – are we making ourselves redundant?” – a thought-provoking session on the evolving role of developers in the age of AI. Speakers & Sessions at Global AI Bootcamp Berlin 2025
What to Expect?
Agenda \| Event Schedule
(Agenda subject to updates.) Global AI BootcampThe Global AI Community connects over 60,000 AI enthusiasts worldwide, fostering learning, collaboration, and skill development. The Global AI Bootcamp is a free, community-driven event dedicated to exploring AI's transformative potential, with a focus on Azure AI and Copilots. Partners, Friends and Communities
Crew and Team
** Important Notice**Photos and videos will be taken during the event for community highlights and social media. If you prefer not to be photographed, please inform the organizers upon arrival. Register & Learn More📌 Claim your Digital Event Badge Code: MRLFHW 📌 Register for the event 📌 Meetup Event Page #GlobalAIBootcamp \| globalai.community |
Global AI Bootcamp {Berlin} | In-person
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Causal Inference for Data Science
2025-01-30
Aleix Ruiz de Villa
– author
When you know the cause of an event, you can affect its outcome. This accessible introduction to causal inference shows you how to determine causality and estimate effects using statistics and machine learning. A/B tests or randomized controlled trials are expensive and often unfeasible in a business environment. Causal Inference for Data Science reveals the techniques and methodologies you can use to identify causes from data, even when no experiment or test has been performed. In Causal Inference for Data Science you will learn how to: Model reality using causal graphs Estimate causal effects using statistical and machine learning techniques Determine when to use A/B tests, causal inference, and machine learning Explain and assess objectives, assumptions, risks, and limitations Determine if you have enough variables for your analysis It’s possible to predict events without knowing what causes them. Understanding causality allows you both to make data-driven predictions and also intervene to affect the outcomes. Causal Inference for Data Science shows you how to build data science tools that can identify the root cause of trends and events. You’ll learn how to interpret historical data, understand customer behaviors, and empower management to apply optimal decisions. About the Technology Why did you get a particular result? What would have lead to a different outcome? These are the essential questions of causal inference. This powerful methodology improves your decisions by connecting cause and effect—even when you can’t run experiments, A/B tests, or expensive controlled trials. About the Book Causal Inference for Data Science introduces techniques to apply causal reasoning to ordinary business scenarios. And with this clearly-written, practical guide, you won’t need advanced statistics or high-level math to put causal inference into practice! By applying a simple approach based on Directed Acyclic Graphs (DAGs), you’ll learn to assess advertising performance, pick productive health treatments, deliver effective product pricing, and more. What's Inside When to use A/B tests, causal inference, and ML Assess objectives, assumptions, risks, and limitations Apply causal inference to real business data About the Reader For data scientists, ML engineers, and statisticians. About the Author Aleix Ruiz de Villa Robert is a data scientist with a PhD in mathematical analysis from the Universitat Autònoma de Barcelona. Quotes With intuitive explanations, application-focused insights, and real-world examples, this book offers immense practical value. - Philipp Bach, Maintainer of the DoubleML libraries for Python and R An essential guide for navigating the complexities of real-world data analysis. - Adi Shavit, SWAPP A must-read! Demystifies causal inference with a blend of theory and practice. - Karan Gupta, SunPower Corporation Causal relationships can mask and distort results. This book provides a set of tools to extract insights correctly. - Peter V. Henstock, Harvard Extension |
O'Reilly Data Science Books
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Peter Carter
– author
All the mistakes you might make with SQL Server—and how to avoid them! 100 SQL Server Mistakes and How to Avoid Them prepares you for the pitfalls database professionals often encounter—from administration to development, availability, and security. You'll learn to sidestep common errors that slow down your T-SQL code and ensure your SQL Server is installed and configured to handle anything your organization throws at it. Inside 100 SQL Server Mistakes and How to Avoid Them you'll learn to avoid: Development errors when writing T-SQL Installation and administration mistakes Optimization missteps Common pitfalls relating to high availability and disaster recovery (HA/DR) Security oversights that can endanger your data 100 SQL Server Mistakes and How to Avoid Them doesn't focus on the "happy path"—instead, it covers all the errors and problems you might face as a SQL Server developer or administrator. Each chapter is filled with real-world issues drawn from author Peter A. Carter’s two-decade-long career in SQL Server. Peter's seasoned advice helps dispel myths, debunk misconceptions, and set you on the right road. About the Technology Perfecting a SQL Server system can be a complex balancing act. Why is T-SQL running so slowly? Are the right data available? Are we protected against data theft? What about that new server instance I need to administer? Even the most skilled SQL Server experts make mistakes that cost time and performance. This book can help you get it right the first time. About the Book 100 SQL Server Mistakes and How to Avoid Them focuses exclusively on the errors that you might—and probably will—make as a SQL Server admin or developer. Real-world examples, code samples, and helpful diagrams make it easy to understand each issue and its solution. You’ll learn how to write performant code, design efficient database schemas, implement error handling, work with complex data types, and much more, all in a friendly, common-sense problem/solution format. What's Inside T-SQL development Installation, administration, and optimization High availability and security About the Reader Readers need to understand basic SQL Server concepts and SQL queries. Perfect for junior database admins, full-stack developers, and “accidental” DBAs. About the Author Peter A. Carter is a SQL Server expert with experience developing, administering, and architecting data-tier applications and SQL Server platforms. Quotes A masterful job! Covers the nuances of SQL Server that a new admin, or even an experienced one, needs to understand. - Allen White, SQL Server MVP 2007-2022 Quick, actionable advice that greatly improved my SQL Server skills. - Ruben Vandeginste, PeopleWare A practical path through pitfalls in administration and development with specific solutions, examples, and code snippets. - Josephine Bush, sqlkitty.com Worth reading for the testing and debugging section alone! - Mike McQuillan, McQTech Ltd. |
O'Reilly SQL Books
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LIMITED SPACES:: Apache Kafka® meets Apache Druid® v2
2024-08-08 · 17:00
Maximum number of attendees in venue space: 40 ppl Join us for this special summer event with the opportunity to learn about how Kafka fits into the analytics space. Please note there are only 40 spaces and entry will be strictly limited to first registered. 👮🏼 Please bring government issued ID to the event as this will be checked by security 🚨 Doors will close at 7:00pm due to security reasons, you will not be able to enter after this time. Date and Time: 🗓️ Thursday August 8th, ⏰ 18:00 - 20:00 🕘 Venue: Confluent Europe Ltd, 262 High Holborn Floor 1 London WC1V 7EJ · London Attending Brands: Imply, Confluent & OSO Networking: Pizza + Beer at the start Schedule: 18:00: Welcome/doors Open, Food, drinks, networking 18:30 - 19:15: “Simplifying Apache Kafka® : Easy Configurations for Immediate Impact” Bethan Hughes, Confluent & Niamh Thornbury, Confluent 19:15 - 20:00pm: “Real-time plane-spotting”, Peter Marshall and Hugh Evans, Imply 20:00- 20:30pm: Additional Q&A & Networking 🎙️ \~Talk 1\~ Talk Title: Simplifying Apache Kafka® : Easy Configurations for Immediate Impact Summary: In the realm of event-driven architecture and real-time data processing, Apache Kafka® stands at the forefront in providing an efficient and scalable solution for handling large volumes of data streams in real-time. However, developers often find interfacing with Apache Kafka® producers and consumers to be a labyrinth of complexities. Are you wasting valuable time deciphering the configuration required for your Apache Kafka® producers and consumers? Whether you require high throughput, low latency, or simply want to start with the fundamentals, our preconfigured profiles streamline and optimize the configuration process to just a few lines of code. Should you require further customization, rest assured that we provide options to modify our configurations according to your specific requirements. In this session we will cover:
🗣️ Speaker 1: Bethan Hughes is an Partner Innovation Engineer at Confluent in the Partner Applied Solutions Integrations team. She has experience building and validating real-time data streaming pipelines which connect to Confluent Cloud and Confluent Platform. 🗣️ Speaker 1: Niamh is a Customer Innovation Engineer who joined Confluent in October 2021. Niamh enjoys spending time with her dog Flo, running and going to the gym. 🎙️ \~Talk 2\~ Talk Title: Real-time plane-spotting Summary: Hidden from our eyes, aircraft in our skies are constantly transmitting data. Join us as we use some simple tech and the power of open source to fly through this data set. In this talk, see a Raspberry Pi, Apache Kafka, Apache Druid, and Grafana coming together for real-time data production, transport, OLAP, and interactive visualisation. 🗣️ Speaker 1: Peter Marshall is an award-winning speaker who leads developer relations at Imply, having worked with adopters and users of Apache Druid for five years. Peter has worked in enterprise architecture in both public and private sector for over 20 years. He has a BA in Theology and Computer Studies from the University of Birmingham. 🗣️ Speaker 2: Hugh Evans is a Developer Advocate at Imply, helping members of the Apache Druid community and bringing them together. DISCLAIMER * WE DO NOT CATER TO THOSE UNDER THE AGE OF 18. *THIS IS AN OFFICE SPACE, PLEASE ENSURE TO CLEAN UP AFTER YOURSELVES AND TAKE CARE OF THIS SPACE. RESPECT THE SPACE AND THOSE IN IT. THIS INCLUDES: NO PHOTOS OF THE OFFICE, NO VANDALISM, GOING OUTSIDE OF THE MEETUP AREA ETC. |
LIMITED SPACES:: Apache Kafka® meets Apache Druid® v2
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Apache Kafka meets Apache Druid
2024-07-23 · 17:00
Join us for this special summer event with the opportunity to learn about how Kafka fits into the analytics space. Please note there are only 70 spaces and entry will be strictly limited to first registered. Date and Time: 🗓️ Tuesday 23rd July, ⏰ 18:00 - 20:00 🕘 Venue: Confluent Europe Ltd, 262 High Holborn Floor 1 London WC1V 7EJ · London Attending Brands: Imply, Streambased, Confluent & OSO Networking: Pizza + Beer at the end Schedule: 18:00: Doors Open, Food, drinks, networking 18:30 - 18:35: Welcome and introductions 18:35 - 19:00: “Kafka - No Rocks, Please”, Roman Kolesnev, Confluent 19:05 - 19:35pm: “Real-time plane-spotting”, Peter Marshall and Hugh Evans, Imply 19:35 - 20:00:“Indexing Kafka - Why point look ups matter and how we achieve them”, Tom Scott, Streambased 🎙️ \~Talk 1\~ Talk Title: Kafka - No Rocks, Please! Summary: Using Kafka Streams With Alternative State StoresA popular data transformation library in the Apache Kafka® world - Kafka Streams - is bundled with a high-performance key/value store - RocksDB - with many advantages regarding near real-time, high throughput, and low latency processing. But what if RocksDB key/value store semantics are just not enough? What if the use case requires features of other storage engines - document indexing, graph processing, or simply secondary indexes? Can we employ other embeddable storage engines or extend RocksDB-based state stores?Luckily, Kafka Streams supports custom state store implementations through a pluggable interface. Even better - we can delegate durability, data sharding, and failure recovery to Kafka Streams runtime. Of course, there are some associated restrictions as well. That, and more, is what we will explore in this session. 🗣️ Speaker: Roman Kolesnev is a Staff Customer Innovation Engineer at Confluent in the Customer Solutions & Innovation Division Labs team. His experience includes building business critical event streaming applications and distributed systems in the financial and technology sectors. 🎙️ \~Talk 2\~ Talk Title: Real-time plane-spotting Summary: Hidden from our eyes, aircraft in our skies are constantly transmitting data. Join us as we use some simple tech and the power of open source to fly through this data set. In this talk, see a Raspberry Pi, Apache Kafka, Apache Druid, and Grafana coming together for real-time data production, transport, OLAP, and interactive visualisation. 🗣️ Speaker 1: Peter Marshall is an award-winning speaker who leads developer relations at Imply, having worked with adopters and users of Apache Druid for five years. Peter has worked in enterprise architecture in both public and private sector for over 20 years. He has a BA in Theology and Computer Studies from the University of Birmingham. 🗣️ Speaker 2: Hugh Evans is a Developer Advocate at Imply, helping members of the Apache Druid community and bringing them together. 🎙️ \~Talk 3\~ Talk Title: Indexing Kafka - Why point look ups matter and how we achieve them Summary: Have you ever wanted to know the count of messages on a topic? How about the count of messages with a particular property? Ever spent long hours searching for that poison pill message that killed your applications? All of these cases require looking at historical data in Kafka, something it is traditionally terrible at. Join us in this talk as we explore historical Kafka data interactively and discuss the technologies that can make this possible. 🗣️ Speaker: Tom Scott is the founder of Streambased, Tom is building multi tenant, on-prem and cloud Kafka services to attack common Kafka pain points and break down barriers to starting your data journey. |
Apache Kafka meets Apache Druid
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Barking Up The Wrong GPTree: Building Better AI With A Cognitive Approach
2024-05-05 · 12:30
Peter Voss
– guest
@ Aigo
,
Tobias Macey
– host
Summary Artificial intelligence has dominated the headlines for several months due to the successes of large language models. This has prompted numerous debates about the possibility of, and timeline for, artificial general intelligence (AGI). Peter Voss has dedicated decades of his life to the pursuit of truly intelligent software through the approach of cognitive AI. In this episode he explains his approach to building AI in a more human-like fashion and the emphasis on learning rather than statistical prediction. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data managementDagster offers a new approach to building and running data platforms and data pipelines. It is an open-source, cloud-native orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. Your team can get up and running in minutes thanks to Dagster Cloud, an enterprise-class hosted solution that offers serverless and hybrid deployments, enhanced security, and on-demand ephemeral test deployments. Go to dataengineeringpodcast.com/dagster today to get started. Your first 30 days are free!Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics. Trusted by teams of all sizes, including Comcast and Doordash, Starburst is a data lake analytics platform that delivers the adaptability and flexibility a lakehouse ecosystem promises. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data. Want to see Starburst in action? Go to dataengineeringpodcast.com/starburst and get $500 in credits to try Starburst Galaxy today, the easiest and fastest way to get started using Trino.Your host is Tobias Macey and today I'm interviewing Peter Voss about what is involved in making your AI applications more "human"Interview IntroductionHow did you get involved in machine learning?Can you start by unpacking the idea of "human-like" AI? How does that contrast with the conception of "AGI"?The applications and limitations of GPT/LLM models have been dominating the popular conversation around AI. How do you see that impacting the overrall ecosystem of ML/AI applications and investment?The fundamental/foundational challenge of every AI use case is sourcing appropriate data. What are the strategies that you have found useful to acquire, evaluate, and prepare data at an appropriate scale to build high quality models? What are the opportunities and limitations of causal modeling techniques for generalized AI models?As AI systems gain more sophistication there is a challenge with establishing and maintaining trust. What are the risks involved in deploying more human-level AI systems and monitoring their reliability?What are the practical/architectural methods necessary to build more cognitive AI systems? How would you characterize the ecosystem of tools/frameworks available for creating, evolving, and maintaining these applications?What are the most interesting, innovative, or unexpected ways that you have seen cognitive AI applied?What are the most interesting, unexpected, or challenging lessons that you have learned while working on desiging/developing cognitive AI systems?When is cognitive AI the wrong choice?What do you have planned for the future of cognitive AI applications at Aigo?Contact Info LinkedInWebsiteParting Question From your perspective, what is the biggest barrier to adoption of machine learning today?Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.init covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning.Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.If you've learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story.Links Aigo.aiArtificial General IntelligenceCognitive AIKnowledge GraphCausal ModelingBayesian StatisticsThinking Fast & Slow by Daniel Kahneman (affiliate link)Agent-Based ModelingReinforcement LearningDARPA 3 Waves of AI presentationWhy Don't We Have AGI Yet? whitepaperConcepts Is All You Need WhitepaperHellen KellerStephen HawkingThe intro and outro music is from Hitman's Lovesong feat. Paola Graziano by The Freak Fandango Orchestra/CC BY-SA 3.0 |
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Mobile Data Collection And Analysis Using Ona And Canopy With Peter Lubell-Doughtie - Episode 41
2018-07-30 · 01:00
Peter Lubell-Doughtie
– CTO
@ Ona
,
Tobias Macey
– host
Summary With the attention being paid to the systems that power large volumes of high velocity data it is easy to forget about the value of data collection at human scales. Ona is a company that is building technologies to support mobile data collection, analysis of the aggregated information, and user-friendly presentations. In this episode CTO Peter Lubell-Doughtie describes the architecture of the platform, the types of environments and use cases where it is being employed, and the value of small data. 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. Are you struggling to keep up with customer request and letting errors slip into production? Want to try some of the innovative ideas in this podcast but don’t have time? DataKitchen’s DataOps software allows your team to quickly iterate and deploy pipelines of code, models, and data sets while improving quality. Unlike a patchwork of manual operations, DataKitchen makes your team shine by providing an end to end DataOps solution with minimal programming that uses the tools you love. Join the DataOps movement and sign up for the newsletter at datakitchen.io/de today. After that learn more about why you should be doing DataOps by listening to the Head Chef in the Data Kitchen at dataengineeringpodcast.com/datakitchen Go to dataengineeringpodcast.com to subscribe to the show, sign up for the mailing list, read the show notes, and get in touch. Join the community in the new Zulip chat workspace at dataengineeringpodcast.com/chat Your host is Tobias Macey and today I’m interviewing Peter Lubell-Doughtie about using Ona for collecting data and processing it with Canopy Interview Introduction How did you get involved in the area of data management? What is Ona and how did the company get started? What are some examples of the types of customers that you work with? What types of data do you support in your collection platform? What are some of the mechanisms that you use to ensure the accuracy of the data that is being collected by users? Does your mobile collection platform allow for anyone to submit data without having to be associated with a given account or organization? What are some of the integration challenges that are unique to the types of data that get collected by mobile field workers? Can you describe the flow of the data from collection through to analysis? To help improve the utility of the data being collected you have started building Canopy. What was the tipping point where it became worth the time and effort to start that project? What are the architectural considerations that you factored in when designing it? What have you found to be the most challenging or unexpected aspects of building an enterprise data warehouse for general users? What are your plans for the future of Ona and Canopy? Contact Info Email pld on Github Website Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Links OpenSRP Ona Canopy Open Data Kit Earth Institute at Columbia University Sustainable Engineering Lab WHO Bill and Melinda Gates Foundation XLSForms PostGIS Kafka Druid Superset Postgres Ansible Docker Terraform The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA Support Data Engineering Podcast |
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Peter Morgan, CEO, Deep Learning Partnership
2017-06-01 · 03:25
Peter Morgan
– CEO
@ Deep Learning Partnership
,
Vishal Kumar
– CEO
@ AnalyticsWeek
In this session Peter Morgan, CEO Deep Learning Partnership sat with Vishal Kumar, CEO AnalyticsWeek and shared his thoughts around Deep Learning, Machine Learning and Artificial Intelligence. They've discussed some of the best practices when it comes to picking right solution, right vendor and what are some of the keyword means. Here's Peter's Bio: Peter Morgan is a scientist-entrepreneur starting out in high energy physics enrolled in the PhD program at the University of Massachusetts at Amherst. After leaving UMass, and founding my own company, Peter has moved into computer networks, designing, implementing and troubleshooting global IP networks for companies such as Cisco, IBM and BT Labs. After getting an MBA and dabbling in financial trading algorithms. Peter has worked for three years on an experiment lead by Stanford University to measure the mass of the neutrino. Since 2012. He had been working in Data Science and Deep Learning, founding an AI Solutions company in Jan 2016. As an entrepreneur Peter has founded companies in the AI, social media, and music industries. He has also served on the advisory board of technology startups. Peter is a popular speaker at conferences, meetups and webinars. He has cofounded and currently organize meetups in the deep learning space. Peter has business experience in the USA, UK and Europe. Today, as CEO of Deep Learning Partnership, He leads the strategic direction and business development across product and services. This includes sales and marketing, lead generation, client engagement, recruitment, content creation and platform development. Deep Learning technologies used include computer vision and natural language processing and frameworks like TensorFlow, Keras and MXnet. Deep Learning Partnership design and implement AI solutions for our clients across all business domains. Interested in sharing your thought leadership with our global listeners? Register your interest @ http://play.analyticsweek.com/guest/ |
The Future of Data Podcast | conversation with leaders, influencers, and change makers in the World of Data & Analytics |
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MongoDB in Action, Second Edition
2016-03-29
Douglas Garrett
– author
,
Shaun Verch
– author
,
Kyle Banker
– author
,
Tim Hawkins
– author
,
Peter Bakkum
– author
GET MORE WITH MANNING An eBook copy of the previous edition, MongoDB in Action (First Edition), is included at no additional cost. It will be automatically added to your Manning Bookshelf within 24 hours of purchase. MongoDB in Action, Second Edition is a completely revised and updated version. It introduces MongoDB 3.0 and the document-oriented database model. This perfectly paced book gives you both the big picture you'll need as a developer and enough low-level detail to satisfy system engineers. About the Technology This document-oriented database was built for high availability, supports rich, dynamic schemas, and lets you easily distribute data across multiple servers. MongoDB 3.0 is flexible, scalable, and very fast, even with big data loads. About the Book MongoDB in Action, Second Edition is a completely revised and updated version. It introduces MongoDB 3.0 and the document-oriented database model. This perfectly paced book gives you both the big picture you'll need as a developer and enough low-level detail to satisfy system engineers. Lots of examples will help you develop confidence in the crucial area of data modeling. You'll also love the deep explanations of each feature, including replication, auto-sharding, and deployment. What's Inside Indexes, queries, and standard DB operations Aggregation and text searching Map-reduce for custom aggregations and reporting Deploying for scale and high availability Updated for Mongo 3.0 About the Reader Written for developers. No previous MongoDB or NoSQL experience is assumed. About the Authors After working at MongoDB, Kyle Banker is now at a startup. Peter Bakkum is a developer with MongoDB expertise. Shaun Verch has worked on the core server team at MongoDB. A Genentech engineer, Doug Garrett is one of the winners of the MongoDB Innovation Award for Analytics. A software architect, Tim Hawkins has led search engineering at Yahoo Europe. Technical Contributor: Wouter Thielen Technical Editor: Mihalis Tsoukalos Quotes A thorough manual for learning, practicing, and implementing MongoDB - Jeet Marwah, Acer Inc. A must-read to properly use MongoDB and model your data in the best possible way. - Hernan Garcia, Betterez Inc. Provides all the necessary details to get you jump-started with MongoDB. - Gregor Zurowski, Independent Software Development Consultant Awesome! MongoDB in a nutshell. - Hardy Ferentschik, Red Hat |
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SQL Server AlwaysOn Revealed
2015-12-09
Peter A Carter
– author
Get a fast start to using AlwaysOn, the SQL Server solution to high-availability and disaster recovery. Read this short, 150-page book that is adapted from Peter Carter’s Pro SQL Server Administration to gain a solid and accurate understanding of how to implement systems requiring consistent and continuous uptime. Begin with an introduction to high-availability and disaster recovery concepts such as Recovery Point Objectives (RPOs), Recovery Time Objectives (RTO), availability levels, and the cost of downtime. Then move into detailed coverage of implementing and configuring the AlwaysOn feature set in order to meet the business objectives set by your organization. offers real-world advice on how to build and configure the most appropriate topology to meet the high-availability and disaster recovery requirements you are faced with. Content includes strong coverage on implementing clusters, on building AlwaysOn failover clustered instances, and on configuring AlwaysOn Availability Groups. This is a practical and hand-on book to get you started quickly in using one of the most talked-about SQL Server feature sets. SQL Server AlwaysOn Revealed Teaches you to build HA and DR solutions using the AlwaysOn feature set Provides real-world advice on configuration and performance considerations Demonstrates administrative techniques for the AlwaysOn feature set |
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Storm Applied
2015-03-31
Storm Applied is a practical guide to using Apache Storm for the real-world tasks associated with processing and analyzing real-time data streams. This immediately useful book starts by building a solid foundation of Storm essentials so that you learn how to think about designing Storm solutions the right way from day one. But it quickly dives into real-world case studies that will bring the novice up to speed with productionizing Storm. About the Technology It's hard to make sense out of data when it's coming at you fast. Like Hadoop, Storm processes large amounts of data but it does it reliably and in real time, guaranteeing that every message will be processed. Storm allows you to scale with your data as it grows, making it an excellent platform to solve your big data problems. About the Book Storm Applied is an example-driven guide to processing and analyzing real-time data streams. This immediately useful book starts by teaching you how to design Storm solutions the right way. Then, it quickly dives into real-world case studies that show you how to scale a high-throughput stream processor, ensure smooth operation within a production cluster, and more. Along the way, you'll learn to use Trident for stateful stream processing, along with other tools from the Storm ecosystem. What's Inside Mapping real problems to Storm components Performance tuning and scaling Practical troubleshooting and debugging Exactly-once processing with Trident About the Reader This book moves through the basics quickly. While prior experience with Storm is not assumed, some experience with big data and real-time systems is helpful. About the Authors Sean Allen, Matthew Jankowski, and Peter Pathirana lead the development team for a high-volume, search-intensive commercial web application at TheLadders. Quotes Will no doubt become the definitive practitioner’s guide for Storm users. - From the Foreword by Andrew Montalenti The book’s practical approach to Storm will save you a lot of hassle and a lot of time. - Tanguy Leroux, Elasticsearch Great introduction to distributed computing with lots of real-world examples. - Shay Elkin, Tangent Logic Go beyond the MapReduce way of thinking to solve big data problems. - Muthusamy Manigandan, OzoneMedia |
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Peter Jones
– author
Deliver SAP BI 7.0 Web Reports Distribute integrated, accurate, and timely data across your enterprise using the Web-based reporting components in SAP BI. Written by an SAP insider, Applied SAP BI 7.0 Web Reports: Using BEx Web Analyzer and Web Application Designer shows you how to construct effective queries, create HTML-based reports, and combine key analytics into a dashboard-style interface. Learn how to import data from multiple providers, configure custom templates, track Key Performance Indicators (KPIs), and incorporate JavaScript and XHTML. Security, troubleshooting, and third-party tools are also discussed in this comprehensive guide. Essential BI skills for business professionals: Define queries and export them as links with BEx Web Analyzer Create BI-specific HTML pages using Web Application Designer and Report Designer Construct reusable templates, shortcuts, and Web items Design high-impact BI dashboards, cockpits, and billboards Integrate toolbars,drilldown capabilities, and drag-and-drop features Publish reporting objects with the Broadcaster and Broadcast Wizard Migrate existing systems and reports to the SAP BI 7.0 platform Add BusinessObjects, Crystal Reports, and JavaScript components Peter Jones, MBA, is a principal/platinum business applications consultant with SAP Professional Services Consulting. He has more than 11 years of consulting and educational experience in a variety of strategic and leadership roles. Jones is the author of SAP Business Information Warehouse Reporting. |
O'Reilly Data Science Books
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Len Silverston
– author
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Paul Agnew
– author
This third volume of the best-selling "Data Model Resource Book" series revolutionizes the data modeling discipline by answering the question "How can you save significant time while improving the quality of any type of data modeling effort?" In contrast to the first two volumes, this new volume focuses on the fundamental, underlying patterns that affect over 50 percent of most data modeling efforts. These patterns can be used to considerably reduce modeling time and cost, to jump-start data modeling efforts, as standards and guidelines to increase data model consistency and quality, and as an objective source against which an enterprise can evaluate data models. Praise for The Data Model Resource Book, Volume 3 "Len and Paul look beneath the superficial issues of data modeling and have produced a work that is a must for every serious designer and manager of an IT project." " The Data Model Resource Book, Volume 3: Universal Patterns for Data Modeling is a great source for reusable patterns you can use to save a tremendous amount of time, effort, and cost on any data modeling effort. Len Silverston and Paul Agnewhave provided an indispensable reference of very high-quality patterns for the most foundational types of datamodel structures. This book represents a revolutionary leap in moving the data modeling profession forward." — Ron Powell, Cofounder and Editorial Director of the Business Intelligence Network "After we model a Customer, Product, or Order, there is still more about each of these that remains to be captured, such as roles they play, classifications in which they belong, or states in which they change. The Data Model Resource Book, Volume 3: Universal Patterns for Data Modeling clearly illustrates these common structures. Len Silverston and Paul Agnew have created a valuable addition to our field, allowing us to improve the consistency and quality of our models by leveraging the many common structures within this text." — Steve Hoberman, Best-Selling Author of Data Modeling Made Simple "The large national health insurance company I work at has actively used these data patterns and the (Universal Data Models) UDM, ahead of this book, through Len Silverston’s UDM Jump Start engagement. The patterns have found their way into the core of our Enterprise Information Model, our data warehouse designs, and progressively into key business function databases. We are getting to reuse the patterns across projects and are reaping benefits in understanding, flexibility, and time-to-market. Thanks so much." — David Chasteen, Enterprise Information Architect "Reusing proven data modeling design patterns means exactly that. Data models become stable, but remain very flexible to accommodate changes. We have had the fortune of having Len and Paul share the patterns that are described in this book via our engagements with Universal Data Models, LLC. These data modeling design patterns have helped us to focus on the essential business issues because we have leveraged these reusable building blocks for many of the standard design problems. These design patterns have also helped us to evaluate the quality of data models for their intended purpose. Many times there are a lot of enhancements required. Too often the very specialized business-oriented data model is also implemented physically. This may have significant drawbacks to flexibility. I’m looking forward to increasing the data modeling design pattern competence within Nokia with the help of this book." — Teemu Mattelmaki, Chief Information Architect, Nokia "Once again, Len Silverston, this time together with Paul Agnew, has made a valuable contribution to the body of knowledge about datamodels, and the act of building sound data models. As a professional data modeler, and teacher of data modeling for almost three decades, I have always been aware that I had developed some familiar mental "patterns" which I acquired very early in my data modeling experience. When teaching data modeling, we use relatively simple workshops, but they are carefully designed so the students will see and acquire a lot of these basic "patterns" — templates that they will recognize and can use to interpret different subject matter into data model form quickly and easily. I’ve always used these patterns in the course of facilitating data modeling sessions; I was able to recognize "Ah, this is just like . . .," and quickly apply a pattern that I’d seen before. But, in all this time, I’ve never sat down and clearly categorized and documented what each of these “patterns’’ actually was in such a way that they could be easily and clearly communicated to others; Len and Paul have done exactly that. As in the other Data Model Resource Books, the thinking and writing is extraordinarily clear and understandable. I personally would have been very proud to have authored this book, and I sincerely applaud Len and Paul for another great contribution to the art and science of data modeling. It will be of great value to any data modeler." — William G. Smith, President, William G. Smith & Associates, www.williamgsmith.com "Len Silverston and Paul Agnew’s book, Universal Patterns for Data Modeling, is essential reading for anyone undertaking commercial datamodeling. With this latest volume that compiles and insightfully describes fundamental, universal data patterns, The Data Model Resource Book series represents the most important contribution to the data modeling discipline in the last decade." — Dr. Graeme Simsion, Author of Data Modeling Essentials and Data Modeling Theory and Practice "Volume 3 of this trilogy is a most welcome addition to Len Silverston’s two previous books in this area. Guidance has existed for some time for those who desire to use pattern-based analysis to jump-start their data modeling efforts. Guidance exists for those who want to use generalized and industry-specific data constructs to leverage their efforts. What has been missing is guidance to those of us needing guidance to complete the roughly one-third of data models that are not generalized or industry-specific. This is where the magic of individual organizational strategies must manifest itself, and Len and Paul have done so clearly and articulately in a manner that complements the first two volumes of The Data Model Resource Book. By adding this book to Volumes 1 and 2 you will be gaining access to some of the most integrated data modeling guidance available on the planet." — Dr. Peter Aiken, Author of XML in Data Management and data management industry leader VCU/Data Blueprint |
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Ph.D. Peter Zielczynski
– author
Optimize Your Entire Requirements Process–and Use Requirements to Build More Successful Software Using IBM® Rational® RequisitePro®, you can systematically improve the way you create and maintain requirements–and use those requirements to build more effective, higher-quality software. Now, for the first time, there’s a comprehensive, hands-on guide to optimally using RequisitePro in real-world development environments. Utilizing a start-to-finish sample project, requirements expert Peter Zielczynski introduces an organized, best-practice approach to managing requirements and shows how to implement every step with RequisitePro. You’ll walk through planning, eliciting, and clarifying stakeholder requirements; building use cases and other key project documents; managing changing requirements; transforming requirements into designs; and much more. Every stage of the process is illuminated with examples, realistic artifacts, and practical solutions. This book is an invaluable resource for everyone who creates requirements, and everyone who relies on them: business analysts, systems analysts, project managers, architects, designers, developers, and testers alike. Coverage includes Overcoming the three leading causes of project failure: lack of user input, incomplete requirements and specifications, and poorly managed change Understanding each type of software requirement–how they interrelate, and what makes a good requirement Establishing a Requirements Management Plan that describes how requirements are created and handled throughout the project lifecycle Developing a Vision document that can drive your project from beginning to end Creating high-quality use cases Using requirements as the basis for system design Leveraging RequisitePro features for improved project management Integrating requirements management with the IBM Rational Unified Process® Foreword xvii Preface xix Acknowledgments xxiii About the Author xxv Part I: Overview 1 Chapter 1: Requirements Management 3 Chapter 2: Overview of RequisitePro 23 Part II: Requirements Management Activities 33 Chapter 3: Establishing a Requirements Management Plan 35 Chapter 4: Setting up the Project 45 Chapter 5: Requirements Elicitation 63 Chapter 6: Developing a Vision Document 99 Chapter 7: Creating Use Cases 129 Chapter 8: Supplementary Specification 157 Chapter 9: Creating Test Cases from Use Cases 191 Chapter 10: Creating Test Cases from Supplementary Requirements 221 Chapter 11: Object-Oriented Design 243 Chapter 12: Documentation 273 Part III: Other Topics 285 Chapter 13: Managing Projects 287 Chapter 14: Requirements Management in the Rational Unified Process 295 Part IV: Review 311 Chapter 15: Summary 313 Appendix: Sample Requirements Management Plan 319 Index 327 |
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J. C. Cannon
– author
Praise for J.C. Cannon's Privacy "A wonderful exploration of the multifaceted work being done to protect the privacy of users, clients, companies, customers, and everyone in between." —Peter Wayner, author of Translucent Databases "Cannon provides an invaluable map to guide developers through the dark forest created by the collision of cutting-edge software development and personal privacy." —Eric Fredericksen, Sr. Software Engineer, PhD., Foundstone, Inc. "Cannon's book is the most comprehensive work today on privacy for managers and developers. I cannot name any technical areas not covered. No practitioners should miss it." —Ray Lai, Principal Engineer, Sun Microsystems, Inc., co-author of Core Security Patterns and author of J2EE Platform Web Services "Every developer should care deeply about privacy and this is the best book I've read on the subject. Get it, read it, and live it." —Keith Ballinger, Program Manager, Advanced Web Services, Microsoft "J.C. Cannon's book demonstrates that information and communication technology can contribute in a significant way to restoring individual privacy and raises more awareness of the complexity and importance of this societal problem." —Dr. John J. Borking, Former Commissioner and Vice-President of the Dutch Data Protection Authority "If you are planning, implementing, coding, or managing a Privacy campaign in your company or your personal computing, there is no more relevant reference. J.C. Cannon nails the issues." —Rick Kingslan, CISSP, Microsoft MVP-Windows Server: Directory Services and Right Management, West Corporation "It's often been said that security is a process, not a product. Privacy is no different! Unlike other privacy books, J.C. Cannon's book has something valuable to convey to everyone involved in the privacy process, from executives to designers and developers, many of whom aren't thinking about privacy but should be." —Keith Brown, Co-founder of Pluralsight and author of The .NET Developer's Guide to Windows Security and Programming Windows Security "J.C. Cannon's new book on electronic privacy is an important addition to the available works in this emerging field of study and practice. Through many humorous (and occasionally frightening) examples of privacy gone wrong, J.C. helps you better understand how to protect your privacy and how to build privacy awareness into your organization and its development process. Keenly illustrating both the pros and cons of various privacy-enhancing and potentially privacy-invading technologies, J.C.'s analysis is thorough and well-balanced. J.C. also explains many of the legal implications of electronic privacy policies and technologies, providing an invaluable domestic and international view." —Steve Riley, Product Manager, Security Business and Technology Unit, Windows Division, Microsoft "Privacy concerns are pervasive in today's high-tech existence. The issues covered by this book should be among the foremost concerns of developers and technology management alike." —Len Sassaman, Security Architect, Anonymizer, Inc. You're responsible for your customers' private information. If you betray their trust, it can destroy your business. Privacy policies are no longer enough. You must make sure your systems truly protect privacy—and it isn't easy. That's where this book comes in. J.C. Cannon, Microsoft's top privacy technology strategist, covers every facet of protecting customer privacy, both technical and organizational. You'll learn how to systematically build privacy safeguards into any application, Web site, or enterprise system, in any environment, on any platform. You'll discover the best practices for building business infrastructure and processes that protect customer privacy. You'll even learn how to help your customers work with you in protecting their own privacy. Coverage includes How privacy and security relate—and why security isn't enough Understanding your legal obligations to protect privacy Contemporary privacy policies, privacy-invasive technologies, and privacy-enhancing solutions Auditing existing systems to identify privacy problem areas Protecting your organization against privacy intrusions Integrating privacy throughout the development process Developing privacy-aware applications: a complete sample application Building a team to promote customer privacy: staffing, training, evangelization, and quick-response Protecting data and databases via role-based access control Using Digital Rights Management to restrict customer information Privacy from the customer's standpoint: spam avoidance, P3P, and other tools and resources Whether you're a manager, IT professional, developer, or security specialist, this book delivers all the information you need to protect your customers—and your organization. The accompanying CD-ROM provides sample privacy-enabling source code and additional privacy resources for developers and managers. J. C. CANNON, privacy strategist at Microsoft's Corporate Privacy Group, specializes in implementing application technologies that maximize consumer control over privacy and enable developers to create privacy-aware applications. He works closely with Microsoft product groups and external developers to help them build privacy into applications. He also contributed the chapter on privacy to Michael Howard's Writing Secure Code (Microsoft Press 2003). Cannon has spent nearly twenty-five years in software development. © Copyright Pearson Education. All rights reserved. |
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