Category: Chapter Meetings

Chapter Meetings

May 2020: Data Prep using Microsoft Dataflows

Presented by Dharmesh Godha, Advaiya

Abstract

Preparing and defining ETL for insights is a significant challenge for businesses today — as ingestion, cleansing, transformation, and enrichment are labor-intensive and time-consuming tasks which require deep technical skills.

With this in mind, Microsoft has recently introduced advanced data prep with dataflows for the Power Platform, a suite of self-service low-code/no-code features and capabilities for business analysts and citizen developers to easily process and unify their data and store it in Azure-based data-lake storage. With these new capabilities, Microsoft offers a solution for any business need — whether you want to prep your data with ease, using a familiar built-in Power Query experience, or leverage the full Azure stack for more advanced use-cases.

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Chapter Meetings

April 2020: MongoDB

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Presented by Jai Karve, MongoDB

Abstract

  • High level “Who is MongoDB”
  • MongoDB Architectural Overview
  • The Document Data Model
  • Intelligently Place Data Where You Need It
  • Freedom to Run Anywhere
  • Live Atlas demonstration

MongoDB has become one of the fastest growing databases since its inception a little over 10 years ago.  In this session, representatives from MongoDB will provide an introduction to the fundamentals of the database, including data storage, data retrieval, and deployment.  We will also walk attendees through a demonstration of Atlas, our fully-managed database-as-a-service.  Attendees will gain a deeper understanding of where MongoDB shines, and how to get started using MongoDB for their own projects.

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Chapter Meetings

March 2020: Data Monetization

NOTE: This event was held remotely via a Zoom bridge at 9:30am Thursday, March 19th

Presented by Justin Langseth

VP of Data Exchange at Snowflake

Abstract TBA

About the Speaker

Justin Langseth is the VP of Data Exchange at Snowflake. He and his team are highly involved in our most “data-forward” customers as it relates to the sharing and monetization of data. Snowflake’s unique architecture and multi-cloud presence allows for streamlined and scalable ways to monetize data through our Data Exchange.

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Chapter Meetings

January 2020: Introduction to Open Source Software in the Enterprise

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Presented by Joanna Lee

Attorney at Gesmer Updegrove LLP

Join us for an introduction to use of Open Source (OS) software in the enterprise. We will learn:

  • What is OS software?
  • Benefits and risks of using OS software
  • Types of OS licenses, which licenses are business-friendly, and how they apply to various use cases
  • Basics of OS compliance and risk management in the enterprise
    Tools for automating compliance

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Chapter Meetings

September 2019: Recent Advances in Natural Language Processing With (Some) Theory & Applications

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Presented by Joachim Rahmfeld, Ph.D

Lecturer at UC Berkeley

Today’s vast volumes of language-based, unstructured, electronic data found in various form factors such as blogs, email, social media, or web sites, promises competitive advantages for those who can extract business-relevant information most effectively and efficiently. Natural Language Processing (NLP) holds the key in leveraging this type of data in order to answer and respond to important questions such as, “What is the perception of my company in the Twittersphere?”, “Are these reviews largely positive or negative?”, “What is the translation of this in Spanish?”, “This document has the answer to my question somewhere… but where?”, “Are these products similar?”

Particularly over the last five years, revolutionary advances in NLP-related Deep Learning algorithms combined with dramatically increased compute resources have created unprecedented opportunities to not only answer natural language questions with greater accuracy and speed, but often also while requiring significantly less training data.

In this session, we will provide an overview of these advances and how you can make use of them. A particular focus will be transfer learning where large, pretrained models, such as Google’s BERT model, can be leveraged for a broad set of NLP use cases delivering excellent results, and enabling you to answer questions that were not possible to answer just a few years ago.

So this is a great time to learn about recent NLP developments and go through explicit examples.

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