Strata Data Conference

Scaling visualization for big data and analytics in the cloud

December 21, 2019

Jaipaul Agonus and Daniel Monteiro do Carmo Rosa detail big data analytics and visualization practices and tools used by FINRA to support machine learning and other surveillance activities that the Market Regulation Department conducts in the AWS cloud.

Scoring your business in the AI matrix (sponsored by Dataiku)

December 21, 2019

One widely accepted definition of AI is that it means going beyond simple statistics to mimic human skills in perception, learning, interaction, and decision making. Jed Dougherty tightens up this definition by sharing examples on a matrix that breaks down the different parts of that definition and how they might manifest themselves in data science projects at different levels.

Serverless for data and AI

December 21, 2019

What is serverless, and how can it be utilized for data analysis and AI? Avner Braverman outlines the benefits and limitations of serverless with respect to data transformation (ETL), AI inference and training, and real-time streaming. This is a technical talk, so expect demos and code.

Serverless workflows for orchestration hybrid cluster-based and serverless processing

December 21, 2019

Serverless implementation of core processing is quickly becoming a production-ready solution. However, companies with existing processing pipelines may find it hard to go completely serverless. Serverless workflows unite the serverless and cluster worlds, with the benefits of both approaches. Rustem Feyzkhanov demonstrates how serverless workflows change your perception of software architecture.

Sharing cancer genomic data from clinical sequencing using the blockchain

December 21, 2019

Sequencing cancer genomes has transformed how we diagnose and treat the deadliest disease in America: cancer. Benjamin Glicksberg explains how coupling cancer genomic data with treatment data through the blockchain will empower patients and citizen scientists to rapidly advance cancer research.

Solving the enterprise data dilemma (sponsored by erwin)

December 21, 2019

Adam Famularo showcases erwin's combination of data management and data governance to produce actionable insights. Erwin customer Nasdaq then shares a real-world use case. You'll learn how to answer tough data questions, how to maintain a metadata landscape, and how to use data management and governance to produce actionable insights.

Spark adaptive execution: Unleash the power of Spark SQL

December 21, 2019

Spark SQL is widely used, but it still suffers from stability and performance challenges in highly dynamic environments with large-scale data. Haifeng Chen shares a Spark adaptive execution engine built to address these challenges. It can handle task parallelism, join conversion, and data skew dynamically during runtime, guaranteeing the best plan is chosen using runtime statistics.

Spark-PMoF: Accelerating big data analytics with Persistent Memory over Fabric

December 21, 2019

Yuan Zhou, Haodong Tang, and Jian Zhang offer an overview of Spark-PMOF and explain how it improves Spark analytics performance.

Strata Data Awards: Winners Announced

December 21, 2019

The Strata Data Awards recognize the most innovative startups, leaders, and data science projects from Strata sponsors and exhibitors around the world. Join us during keynotes for the announcement of the winners.

Streamlining your data assets: A strategy for the journey to AI (sponsored by IBM)

December 21, 2019

The journey to AI begins with data and making intelligent use of it. Dinesh Nirmal shares a strategic framework for streamlining your data assets, a framework that takes into account the current state of your existing data structures, the new technologies driving enterprise, the complexities of business processes, and at the foundation, the elements required in an AI-fluent data platform.

Testing ad content with survey experiments

December 20, 2019

Brands that test the content of ads before they are shown to an audience can avoid spending resources on the 11% of ads that cause backlash. Using a survey experiment to choose the best ad typically improves effectiveness of marketing campaigns by 13% on average, and up to 37% for particular demographics. Patrick Miller explores data collection and statistical methods for analysis and reporting.

The enterprise data cloud

December 20, 2019

Most enterprises want the same flexibility and convenience they get in the public cloud, no matter where their data lives or their applications run. We've reached the point that the "enterprise data cloud" must span the firewall and the services offered by hyperscale vendors. Mike Olson describes the key capabilities that such a system requires and why hybrid and multicloud is the future.

The ethics of analytics

December 20, 2019

Concerns are constantly being raised today about what data is appropriate to collect and how (or if) it should be analyzed. There are many ethical, privacy, and legal issues to consider, and no clear standards exist in many cases as to what is fair and what is foul. Bill Franks explores a variety of dilemmas and provides some guidance on how to approach them.

The future of the firm: Starting now

December 20, 2019

Josh Bersin explains how firms are transforming for the digital era, covering the death of the traditional organizational hierarchy, new models of leadership and management, changes in the way people learn and progress, new models of pay, and the importance of trust and transparency as a central business value.

The journey to the data-driven enterprise from the edge to AI

December 20, 2019

Cloudera drinks its own champagnerunning Cloudera on Cloudera. The company analyzes data from the edge and runs probabilistic models to tune its business processes with AI, from marketing, sales, and support to strategic planning. Amy O'Connor shares what Cloudera has learned from the edge to AI and explains how it's helping Cloudera and its customers get better at data-driven.

The journey toward a self-service data platform at Netflix

December 20, 2019

The Netflix data platform is a massive-scale, cloud-only suite of tools and technologies. It includes big data tech (Spark and Flink), enabling services (federated metadata management), and machine learning support. But with power comes complexity. Kurt Brown explains how Netflix is working toward an easier, "self-service" data platform without sacrificing any enabling capabilities.

The magic behind your Lyft ride prices: A case study on machine learning and streaming

December 20, 2019

Rakesh Kumar and Thomas Weise explore how Lyft dynamically prices its rides with a combination of various data sources, ML models, and streaming infrastructure for low latency, reliability, and scalabilityallowing the pricing system to be more adaptable to real-world changes.

The new frontier: Marshs data voyage into the public cloud (sponsored by Impetus)

December 20, 2019

Stephen Dantu shares insurance broker Marshs pioneering journey into the public cloud and explains why this move was necessary to unleash new opportunities and future-proof the company.

User-based real-time product recommendations leveraging deep learning using Analytics Zoo on Apache Spark and BigDL

December 20, 2019

User-based real-time recommendation systems have become an important topic in ecommerce. Lu Wang, Nicole Kong, Guoqiong Song, and Maneesha Bhalla demonstrate how to build deep learning algorithms using Analytics Zoo with BigDL on Apache Spark and create an end-to-end system to serve real-time product recommendations.

Using the full spectrum of data science to drive business decisions

December 19, 2019

Thanks to the rapid growth in data resources, business leaders now appreciate the importance (and the challenge) of mining information from data. Join in as a group of LinkedIn's data scientists share their experiences successfully leveraging emerging techniques to assist in intelligent decision making.

What the reproducibility problem means for your business

December 19, 2019

Academic research has been plagued by a reproducibility crisis in fields ranging from medicine to psychology. Stuart Buck explains how to take precautions in your data analysis and experiments so as to avoid those reproducibility problems.

When self-service BI meets geospatial analysis

December 19, 2019

In the analysis of the mobile world, everyone starts with the question, "Where?" SK Telecom is trying to meet these needs. Kyungtaak Noh explains how the company provides geospatial analysis by processing geospatial data through Druid with Lucene.

When SQL users run wild: Resource management features and techniques to tame Apache Impala

December 19, 2019