Ben Welsh Keynote
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The document introduces the Los Angeles Times Data Desk, a team that analyzes databases and turns them into news stories. The Data Desk writes code to analyze datasets on topics like vaccination rates, electricity capacity, and campaign finance. They publish code, data, and stories on GitHub and the LA Times website. The goal is to transform raw data into insights that explain issues and hold institutions accountable.
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Presentation given at the CILIP Cataloguing and Indexing Group Conference 2014 "The Impact of Metadata" #cig14 on Monday 8 September 2014 at the University of Kent, Canterbury.
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http://www.cilip.org.uk/cataloguing-and-indexing-group/events/linked-data-what-cataloguers-need-know-cig-event
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2012 07 ictk-johanneskeizer
This document summarizes a presentation by Dr. Johannes Keizer on information dynamics for agricultural research and development. The presentation discussed changing dynamics in how agricultural knowledge is aggregated, researched, distributed geographically, and accessed. It proposed linking previously isolated data sources to facilitate access to real-time information and encourage collaboration. Demonstrators including OpenAgris and linked open vocabularies were presented as examples of how semantic web technologies can help integrate agricultural information and knowledge.
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BIBFRAME
From: Linked Data: what cataloguers need to know. A CIG event. 25 November 2013, Birmingham. #cigld
http://www.cilip.org.uk/cataloguing-and-indexing-group/events/linked-data-what-cataloguers-need-know-cig-event
Accompanying write-up from Catalogue & Index 174: http://discovery.ucl.ac.uk/1449460/
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Robust Links - a proposed solution to reference rot in scholarly communication
Robust Links - a proposed solution to reference rot in scholarly communication
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The Accidental Cataloger: Tips & Tools to Help You Use the Rules
Let's Make Open Data Awesome! (SXSW 2016 Proposal)
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MongoDB is now a Developer Data Platform. Come learn what�s new in the 6.0 release and Atlas following all the recent announcements made at MongoDB World 2022. Topics will include
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- Atlas Data Federation to seamlessly query, transform, and aggregate data from one or more MongoDB Atlas databases, Atlas Data Lake and AWS S3 buckets
- Queryable Encryption lets you run expressive queries on fully randomized encrypted data to meet the most stringent security requirements
- Relational Migrator which analyzes your existing relational schemas and helps you design a new MongoDB schema.
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1. Shopkick has over 30M downloads, but the userbase is very heterogeneous. Anecdotal evidence indicated a wide variety of users for whom the app holds long-term appeal.
2. Marketing and other teams challenged Analytics to get beyond basic summary statistics and develop a holistic segmentation of the userbase.
3. Shopkick's data science team used SQL and python to gather data, clean data, and then perform a data-driven segmentation using a k-means algorithm.
4. Interpreting the results is more work -- and more fun -- than running the algo itself. We'll discuss how we transform from ""segment 1"", ""segment 2"", etc. to something that non-analytics users (Marketing, Operations, etc.) could actually benefit from.
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TurboTax is one of the well known consumer software brand which at its peak serves 385K+ concurrent users. In this session, We start with looking at how user behavioral data & tax domain events are captured in real time using the event bus and analyzed to drive real time personalization with various TurboTax data pipelines. We will also look at solutions performing analytics which make use of these events, with the help of Kafka, Apache Flink, Apache Beam, Spark, Amazon S3, Amazon EMR, Redshift, Athena and Amazon lambda functions. Finally, we look at how SageMaker is used to create the TurboTax model to predict if a customer is at risk or needs help.
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Data Con LA 2022 - Intro to Data Science
Zia Khan, Computer Systems Analyst and Data Scientist at LearningFuze
Data Science tutorial is designed for people who are new to Data Science. This is a beginner level session so no prior coding or technical knowledge is required. Just bring your laptop with WiFi capability. The session starts with a review of what is data science, the amount of data we generate and how companies are using that data to get insight. We will pick a business use case, define the data science process, followed by hands-on lab using python and Jupyter notebook. During the hands-on portion we will work with pandas, numpy, matplotlib and sklearn modules and use a machine learning algorithm to approach the business use case.
Data Con LA 2022 - How are NFTs and DeFi Changing Entertainment
Mariana Danilovic, Managing Director at Infiom, LLC
We will address:
(1) Community creation and engagement using tokens and NFTs
(2) Organization of DAO structures and ways to incentivize Web3 communities
(3) DeFi business models applied to Web3 ventures
(4) Why Metaverse matters for new entertainment and community engagement models.
Data Con LA 2022 - Why Data Quality vigilance requires an End-to-End, Automat...
Curtis ODell, Global Director Data Integrity at Tricentis
Join me to learn about a new end-to-end data testing approach designed for modern data pipelines that fills dangerous gaps left by traditional data management tools—one designed to handle structured and unstructured data from any source. You'll hear how you can use unique automation technology to reach up to 90 percent test coverage rates and deliver trustworthy analytical and operational data at scale. Several real world use cases from major banks/finance, insurance, health analytics, and Snowflake examples will be presented.
Key Learning Objective
1. Data journeys are complex and you have to ensure integrity of the data end to end across this journey from source to end reporting for compliance
2. Data Management tools do not test data, they profile and monitor at best, and leave serious gaps in your data testing coverage
3. Automation with integration to DevOps and DataOps' CI/CD processes are key to solving this.
4. How this approach has impact in your vertical
Data Con LA 2022-Perfect Viral Ad prediction of Superbowl 2022 using Tease, T...
1. The document discusses methods for predicting and engineering viral Super Bowl ads, including a panel-based analysis of video content characteristics and a deep learning model measuring social media effects.
2. It provides examples of ads from Super Bowl 2022 that scored well using these methods, such as BMW and Budweiser ads, and compares predicted viral rankings to actual results.
3. The document also demonstrates how to systematically test, tweak, and target an ad campaign like Bajaj Pulsar's to increase virality through modifications to title, thumbnail, tags and content based on audience feedback.
Data Con LA 2022- Embedding medical journeys with machine learning to improve...
Jai Bansal, Senior Manager, Data Science at Aetna
This talk describes an internal data product called Member Embeddings that facilitates modeling of member medical journeys with machine learning.
Medical claims are the key data source we use to understand health journeys at Aetna. Claims are the data artifacts that result from our members' interactions with the healthcare system. Claims contain data like the amount the provider billed, the place of service, and provider specialty. The primary medical information in a claim is represented in codes that indicate the diagnoses, procedures, or drugs for which a member was billed. These codes give us a semi-structured view into the medical reason for each claim and so contain rich information about members' health journeys. However, since the codes themselves are categorical and high-dimensional (10K cardinality), it's challenging to extract insight or predictive power directly from the raw codes on a claim.
To transform claim codes into a more useful format for machine learning, we turned to the concept of embeddings. Word embeddings are widely used in natural language processing to provide numeric vector representations of individual words.
We use a similar approach with our claims data. We treat each claim code as a word or token and use embedding algorithms to learn lower-dimensional vector representations that preserve the original high-dimensional semantic meaning.
This process converts the categorical features into dense numeric representations. In our case, we use sequences of anonymized member claim diagnosis, procedure, and drug codes as training data. We tested a variety of algorithms to learn embeddings for each type of claim code.
We found that the trained embeddings showed relationships between codes that were reasonable from the point of view of subject matter experts. In addition, using the embeddings to predict future healthcare-related events outperformed other basic features, making this tool an easy way to improve predictive model performance and save data scientist time.
Data Con LA 2022 - Data Streaming with Kafka
Jie Chen, Manager Advisory, KPMG
Data is the new oil. However, many organizations have fragmented data in siloed line of businesses. In this topic, we will focus on identifying the legacy patterns and their limitations and introducing the new patterns packed by Kafka's core design ideas. The goal is to tirelessly pursue better solutions for organizations to overcome the bottleneck in data pipelines and modernize the digital assets for ready to scale their businesses. In summary, we will walk through three uses cases, recommend Dos and Donts, Take aways for Data Engineers, Data Scientist, Data architect in developing forefront data oriented skills.
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Data Con LA 2022 - Using Google trends data to build product recommendations
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Data Con LA 2022 - Improving disaster response with machine learning
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Data Con LA 2022 - What's new with MongoDB 6.0 and Atlas
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Data Con LA 2022 - Real world consumer segmentation
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Data Con LA 2022 - Modernizing Analytics & AI for today's needs: Intuit Turbo...
Data Con LA 2022 - Modernizing Analytics & AI for today's needs: Intuit Turbo...
Data Con LA 2022 - Collaborative Data Exploration using Conversational AI
Data Con LA 2022 - Collaborative Data Exploration using Conversational AI
Data Con LA 2022 - Why Database Modernization Makes Your Data Decisions More ...
Data Con LA 2022 - Why Database Modernization Makes Your Data Decisions More ...
Data Con LA 2022 - How are NFTs and DeFi Changing Entertainment
Data Con LA 2022 - How are NFTs and DeFi Changing Entertainment
Data Con LA 2022 - Why Data Quality vigilance requires an End-to-End, Automat...
Data Con LA 2022 - Why Data Quality vigilance requires an End-to-End, Automat...
Data Con LA 2022-Perfect Viral Ad prediction of Superbowl 2022 using Tease, T...
Data Con LA 2022-Perfect Viral Ad prediction of Superbowl 2022 using Tease, T...
Data Con LA 2022- Embedding medical journeys with machine learning to improve...
Data Con LA 2022- Embedding medical journeys with machine learning to improve...
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Paper: https://doi.org/10.1007/978-3-031-61000-4_16
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Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
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Ben Welsh Keynote
- 1. WHAT IS A A brief tutorial DATA DESK?
- 2. My name is Ben I sometimes go by @palewire
- 3. All my slides are belong to lat.ms/whoisdatadesk
- 4. I work at @latimes in #DTLA
- 5. We turn databases into news Our team is called the Data Desk
- 7. All kinds of code
- 22. https://github.com/datadesk/california-kindergarten-vaccination-analysis/blob/master/analysis.ipynb
- 34. We turn news into databases
- 45. We turn news into software
- 46. And vice versa
- 58. PLUS
- 59. LONGFORM
- 60. BOTS
- 61. TOOLS
- 62. TOYS
- 63. THE END
- 65. All my slides are belong to lat.ms/whoisdatadesk