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Data Con LA

Big Data Day LA 2017

Technologie

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Mike Limcaco, Analytics Specialist / Customer Engineer at Google Measure trends in a particular topic or search term across Google Search across the US down to the city-level. Integrate these data signals into analytic pipelines to drive product, retail, media (video, audio, digital content) recommendations tailored to your audience segment. We'll discuss how Google unique datasets can be used with Google Cloud smart analytic services to process, enrich and surface the most relevant product or content that matches the ever-changing interests of your local customer segment.

Data Con LA 2022 - Using Google trends data to build product recommendations

Data Con LA

Melinda Thielbar, Data Science Practice Lead and Director of Data Science at Fidelity Investments From corporations to governments to private individuals, most of the AI community has recognized the growing need to incorporate ethics into the development and maintenance of AI models. Much of the current discussion, though, is meant for leaders and managers. This talk is directed to data scientists, data engineers, ML Ops specialists, and anyone else who is responsible for the hands-on, day-to-day of work building, productionalizing, and maintaining AI models. We'll give a short overview of the business case for why technical AI expertise is critical to developing an AI Ethics strategy. Then we'll discuss the technical problems that cause AI models to behave unethically, how to detect problems at all phases of model development, and the tools and techniques that are available to support technical teams in Ethical AI development.

Data Con LA 2022 - AI Ethics

Data Con LA

Antje Barth, Principal Developer Advocate, AI/ML at AWS & Chris Fregly, Principal Engineer, AI & ML at AWS The frequency and severity of natural disasters are increasing. In response, governments, businesses, nonprofits, and international organizations are placing more emphasis on disaster preparedness and response. Many organizations are accelerating their efforts to make their data publicly available for others to use. Repositories such as the Registry of Open Data on AWS and Humanitarian Data Exchange contain troves of data available for use by developers, data scientists, and machine learning practitioners. In this session, see how a community of developers came together though the AWS Disaster Response hackathon to build models to support natural disaster preparedness and response.

Data Con LA 2022 - Improving disaster response with machine learning

Data Con LA

Sig Narvaez, Executive Solution Architect at MongoDB MongoDB is now a Developer Data Platform. Come learn whatï¿½s new in the 6.0 release and Atlas following all the recent announcements made at MongoDB World 2022. Topics will include - Atlas Search which combines 3 systems into one (database, search engine, and sync mechanisms) letting you focus on your product's differentiation. - 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. - And more!

Data Con LA 2022 - What's new with MongoDB 6.0 and Atlas

Data Con LA

Jaysen Gillespie, Head of Analytics and Data Science at RTB House 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. 5. So what? How did team across Shopkick change their approach given what Analytics had discovered.

Data Con LA 2022 - Real world consumer segmentation

Data Con LA

Ravi Pillala, Chief Data Architect & Distinguished Engineer at Intuit 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.

Data Con LA 2022 - Modernizing Analytics & AI for today's needs: Intuit Turbo...

Data Con LA

Data Con LA 2022 - Moving Data at Scale to AWS

Data Con LA

Anand Ranganathan, Chief AI Officer at Unscrambl Conversational AI is getting more and more widely used for customer support and employee support use-cases. In this session, I'm going to talk about how it can be extended for data analysis and data science use-cases ... i.e., how users can interact with a bot to ask analytical questions on data in relational databases. This allows users to explore complex datasets using a combination of text and voice questions, in natural language, and then get back results in a combination of natural language and visualizations. Furthermore, it allows collaborative exploration of data by a group of users in a channel in platforms like Microsoft Teams, Slack or Google Chat. For example, a group of users in a channel can ask questions to a bot in plain English like ""How many cases of Covid were there in the last 2 months by state and gender"" or ""Why did the number of deaths from Covid increase in May 2022"", and jointly look at the results that come back. This facilitates data awareness, data-driven collaboration and joint decision making among teams in enterprises and outside. In this talk, I'll describe how we can bring together various features including natural-language understanding, NL-to-SQL translation, dialog management, data story-telling, semantic modeling of data and augmented analytics to facilitate collaborate exploration of data using conversational AI.

Data Con LA 2022 - Collaborative Data Exploration using Conversational AI

Data Con LA

Anil Inamdar, VP & Head of Data Solutions at Instaclustr The most modernized enterprises utilize polyglot architecture, applying the best-suited database technologies to each of their organization's particular use cases. To successfully implement such an architecture, though, you need a thorough knowledge of the expansive NoSQL data technologies now available. Attendees of this Data Con LA presentation will come away with: -- A solid understanding of the decision-making process that should go into vetting NoSQL technologies and how to plan out their data modernization initiatives and migrations. -- They will learn the types of functionality that best match the strengths of NoSQL key-value stores, graph databases, columnar databases, document-type databases, time-series databases, and more. -- Attendees will also understand how to navigate database technology licensing concerns, and to recognize the types of vendors they'll encounter across the NoSQL ecosystem. This includes sniffing out open-core vendors that may advertise as â€œopen source,"" but are driven by a business model that hinges on achieving proprietary lock-in. -- Attendees will also learn to determine if vendors offer open-code solutions that apply restrictive licensing, or if they support true open source technologies like Hadoop, Cassandra, Kafka, OpenSearch, Redis, Spark, and many more that offer total portability and true freedom of use.

Data Con LA 2022 - Why Database Modernization Makes Your Data Decisions More ...

Data Con LA

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 - Intro to Data Science

Data Con LA

Data Con LA 2022 - How are NFTs and DeFi Changing Entertainment

Data Con LA

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 toolsâ€”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 - Why Data Quality vigilance requires an End-to-End, Automat...

Data Con LA

Arif Ansari, Professor at University of Southern California Super Bowl Ad cost $7 million and each year a few Super Bowl ads go viral. The traditional A/B testing does not predict virality. Some highly shared ones reach over 60 million organic views, which can be more valuable than views on TV. Not only are these voluntary, but they are typically without distraction, and win viewer engagement in the form of likes, comments, or shares. A Super Bowl ad that wins 69 million views on YouTube (e.g., Alexa Mind Reader) costs less than 10 cents per quality view! However, the challenge is triggering virality. We developed a method to predict virality and engineer virality into Ads. 1. Prof. Gerard J. Tellis and co-authors recommended that advertisers use YouTube to tease, test, and tweak (TTT) their ads to maximize sharing and viewing. 2022 saw that maxim put into practice. 2. We developed viral Ads prediction using two scientific models: a. Prof. Gerard Tellis et al.'s model for viral prediction b. Deep Learning viral prediction using social media effect 3. The model was able to identify all the top 15 Viral Ads it performed better than the traditional agencies. 4. New proposed method is Tease, Test, Tweak, Target and Spots Ad.

Data Con LA 2022-Perfect Viral Ad prediction of Superbowl 2022 using Tease, T...

Data Con LA

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- Embedding medical journeys with machine learning to improve...

Data Con LA

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.

Data Con LA 2022 - Data Streaming with Kafka

Data Con LA

Xuanzi Han, Senior Software Engineer at Monte Carlo For modern data teams, lineage is a critical component of the data pipeline root cause and impact analysis workflow, as well as a means of ensuring that data, models, and other data assets are healthy and reliable. That being said, the complexity of SQL queries can make it challenging to build lineage manually, particularly at the field level. Xuanzi Han, a member of Monte Carlo's data and product teams, tackled this challenge head-on by leveraging some of the most popular tools in the modern data stack, including dbt, Airflow, Snowflake, and ANother Tool for Language Recognition (ANTLR). In this talk, they share how they designed the data model, query parser, and larger database design for field-level lineage, highlighting learnings, wrong turns, and best practices developed along the way.

Data Con LA 2022 - Building Field-level Lineage from Scratch for Modern Data ...

Data Con LA

David Sarabia, Founder/ CEO at inRecovery & Sig Narvaez, Executive Solution Architect at MongoDB As a bullied kid, I found refuge in computers and taught myself to code at 8. By 26, I had two successful tech exits and moved to NYC. A weekend party habit led to daily drug use and a spiral to heroin and homelessness. In 2016, after a friendï¿½s overdose woke me up. I checked myself into rehab and quickly realized I was there for a bigger purpose. Healthcare is very broken. From legacy systems, inefficiencies, and poor customer experience. What if we could dramatically improve care models by leveraging data, personalizing treatment, and creating beautiful patient experiences? Ever worked in an industry that felt antiquated? Learn how we use MongoDB to transform addiction care and help people thrive in life!

Data Con LA 2022 - Finding true purpose after falling to addiction, and inspi...

Data Con LA

Frank Bell, Data Thought Leader and Snowflake SME at Accenture - CEO at ITS We will cover all aspects of optimizing your Snowflake Data Cloud including: *Dive deep into how Snowflake pay as you go costs work and how by utilizing our proven optimization tools - Snoptimizer SaaS Snowflake Optimizer - https://snoptimizer.com/ , scripts, and architecture techniques you typically can save 10-40++% on your existing Snowflake Account costs. *Explain how Snowflake Compute works and proven techniques on how to architect warehouses for both cost and performance efficiency. We cover in depth how snowflake scales BOTH out and in as well as up and down with compute resources. *Explain how Snowflake data storage works with Replication, Time-Travel, and Cloning. We explain these awesome features as well as their downsides if they are used and configured wrongly. *Cover Snowflake cloud services costs and features that have costs related to them, including Snowpipe, Search Optimization, Materialized Views, Auto-clustering, and other recent new cost based features that provide value at a cost. *Finally, we will discuss how you can ensure your Snowflake Account(s) are fully optimized not just for cost but also for security and performance on Snowflake. We will show you security and performance best practices as well as pitfalls to avoid.

Data Con LA 2022 - Supercharge your Snowflake Data Cloud from a Snowflake Dat...

Data Con LA

Michael Melore, Senior Cybersecurity Advisor, IBM The session will include views from the panel (and myself) * Review the current challenges, volumes of events, staffing shortages, expertise deficiencies, siloed security controls, * Provide statistics from recent Ponemon Institute reports including the recent Cost of a Data Breach 2021 Report's findings in attack vectors, response/organizational impact and costs attributed to remote workforces, * Provide The impact in cost and response times of AI/Machine Learning etc. * Share the way's AI is used in law enforcement and critical infrastructure protection, * Discuss AI bias and evolving Trust and Validation requirements in AI systems, the necessity and value of AI insight to security and where the industry is moving in AI for security.

Data Con LA 2022 - The Evolution of AI in Cybersecurity

Data Con LA

Mark Quinsland, Sr. Field Engineer at Neo4j Luxury yachts, football teams, and mansions are no longer safe havens for the illicit profits of Russian Oligarchs with ties to Putin. Assets are being identified and seized with benefits flowing to causes in Ukraine. This presentation covers: - How are friends and relatives of Putin sheltering immense profits - Graphs and other tools being used to identify sources & destinations of illicit wealth - Latest asset seizures - New regulations to expose hidden investors

Data Con LA 2022 - Who Owns That Yacht? How Graphs Are Used to Identify Asset...

Data Con LA

Plus de Data Con LA (20)

Data Con LA 2022 - Using Google trends data to build product recommendations

Data Con LA 2022 - AI Ethics

Data Con LA 2022 - Improving disaster response with machine learning

Data Con LA 2022 - What's new with MongoDB 6.0 and Atlas

Data Con LA 2022 - Real world consumer segmentation

Data Con LA 2022 - Modernizing Analytics & AI for today's needs: Intuit Turbo...

Data Con LA 2022 - Moving Data at Scale to AWS

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 - Intro to Data Science

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-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 - Data Streaming with Kafka

Data Con LA 2022 - Building Field-level Lineage from Scratch for Modern Data ...

Data Con LA 2022 - Finding true purpose after falling to addiction, and inspi...

Data Con LA 2022 - Supercharge your Snowflake Data Cloud from a Snowflake Dat...

Data Con LA 2022 - The Evolution of AI in Cybersecurity

Data Con LA 2022 - Who Owns That Yacht? How Graphs Are Used to Identify Asset...