The inaugural Datanova conference will feature solutions and architectures to help companies get maximum value from their data.
By Jenn Webb and Ben Lorica.
Since the advent of the first big data management systems over a decade ago, the trends that led to the rise of big data technologies have accelerated. Companies today are facing the challenge of analyzing unprecedented amounts and types of data from new and disparate sources. The rise of machine learning and the internet of things has ushered in streams of unstructured data that companies need to analyze using novel approaches, such as deep learning models within natural language, computer vision, and speech technologies.
The demand companies face to achieve a 360-degree customer view is compounded by a growing consumer expectation for real-time engagement and up-to-the-minute data. This trend requires not only data scientists, data engineers, and analysts to engage with data, but people working across the company in areas like business intelligence, marketing, and sales. New tools are emerging to accommodate these users who aren’t trained in data science, essentially democratizing data analysis.
Solutions
The inaugural Datanova conference, a virtual event presented by Starburst on February 9-10, 2021, will showcase cutting-edge solutions and architectures companies are using to optimize their data platforms. Teams and individuals interested in new ways to unlock value in all of their data can register for free (space is limited).
Data Architecture
For attendees interested in modern data management paradigms, a series of talks cover new architectures, open source projects, and emerging solutions. Highlights include:
- Data Mesh Architecture Part 1: What is it? and Data Mesh Architecture Part 2: How to build it: In these two sessions, Zhamak Dehghani of Thoughtworks introduces data mesh, a new architecture designed to enable companies to pull together data sources without having to do the extract, transform, load (ETL) work. This should be familiar to users of Trino (formerly known as Presto® SQL), as it is well suited for low-latency interactive analytics in data mesh architectures.
- Oxford Debate: Warehouse, Lakehouse, or Lake?: In this session, a panel of experts debate the merits of each model, and its potential to prevail as the best practice for data storage.
- Hybrid Analytics: Ground to Cloud & Cloud to Cloud: Speakers from Comcast describe their approach to hybrid (cloud and on-premise) analytics, and explain why they chose that architecture.
- Confessions of a Cloud Migration: Michelle Ullford, who led data platform engineering teams at Netflix and GoDaddy, shares advice on how to execute cloud migration projects.
Technical Track: Trino and Starburst Solutions
For engineers, architects, and other attendees who are looking for technical sessions, Datanova features presentations from several of Trino’s co-creators and Starburst engineers. Trino (formerly known as Presto® SQL) is one of the most popular tools for big data analytics. This track showcases new tools that facilitate decision-making using all of a company’s data, no matter where it lives. Highlights include:
- Trino, SQL, and Accelerating Data Science: Leading data scientist Paco Nathan moderates a panel on how Trino helps data science and data engineering teams analyze large amounts of data from a variety of data sources and formats. The panel of experts includes the Trino co-creators: Martin Traverso, Dain Sundstrom, and David Phillips.
- Tuning Queries on your Presto® Cluster: In this hands-on lab guided by the Presto® co-creators, attendees can run queries and learn how to debug and improve query performance.
- New Starburst Product Announcement and Demonstration: In this session, Starburst unveils a new way to unify data: users will soon be able to run federated searches and perform data migrations over Snowflake and AWS Redshift without affecting operations.
Thought Leadership
For CEO’s, directors, managers and other decision-makers, Datanova features talks on company culture trends and emerging best practices for organizations. Highlights include:
- The Data Literacy Imperative: Leading data scientist Kirk Borne describes how data literacy can bring value to your business, and suggests ways to promote data literacy inside an organization.
- Drive Digital Transformation Faster with X Analytics: Justin Borgman of Starburst and Sudhir Hasbe of Google discuss “X Analytics”—the analysis of a wide range (“X”) of data, including structured and unstructured data from sources like text, video, and audio. Borgman and Hasbe explain what X Analytics means for an organization, who is doing it, and the modern data architecture you need to support it.
- Bill Nye, the Science Guy: Bill Nye, CEO of The Planetary Society, discusses ways to foster a scientifically literate society by making science entertaining and accessible.
Register for the virtual Datanova conference, February 9-10, 2021.
This post is part of a collaboration between Gradient Flow and Starburst. See our statement of editorial independence.
Main image by Storyblocks