DATE: October 5, 2022, This event has passed. The recordings and slides will be made available On Demand within the next week of the live event.
TIME: 8:00 AM – 12:45 PM Pacific / 11:00 AM – 3:45 PM Eastern
PRICE: Free to all attendees
Welcome to DATAVERSITY Demo Day, an online exhibit hall. We’ve had many requests from our data-driven community for a vendor-driven online event that gives you an opportunity to learn more about the available tools and services directly from the vendors that could contribute to your Data Management program’s success.
Register to attend one or all of the sessions, or in order to receive the follow-up email with links to the slides and recordings.
Session 1: Orchestrate the Real-time Flow of Data Across Data Pipelines
With the aid of any number of data management and processing tools, data flows through multiple on-prem and cloud storage locations before it’s delivered to business users. As a result, IT teams — including IT Ops, DataOps, and DevOps — are often overwhelmed by the complexity of creating a reliable data pipeline that includes the automation and observability they require.
The answer to this widespread problem is a centralized data pipeline orchestration solution.
Join Stonebranch’s Scott Davis, Global Vice President and Ravi Murugesan, Sr. Solution Engineer to learn how DataOps teams orchestrate their end-to-end data pipelines with a platform approach to managing automation.
Key Learnings:
- Discover how to orchestrate data pipelines across a hybrid IT environment (on-prem and cloud)
- Find out how DataOps teams are empowered with event-based triggers for real-time data flow
- See examples of reports, dashboards, and proactive alerts designed to help you reliably keep data flowing through your business — with the observability you require
- Discover how to replace clunky legacy approaches to streaming data in a multi-cloud environment
- See what’s possible with the Stonebranch Universal Automation Center (UAC)
Session 2: Are You Making Decisions with Only 10% of Your Cloud Data?
As much as 90 percent of an organization’s data is unstructured.
From email and documents to media and messaging apps (think: Slack and Teams), the sheer volume and complexity of unstructured cloud data is a growing challenge for IT teams. Join this webinar to discover how IT leaders are leveraging Onna to find, manage, and transform their siloed, unstructured data into actionable knowledge that moves business forward. Bonus? You’ll be among the first to receive an inside look at Onna’s newest product offering coming in early 2023.
Session 3: Analytics with No Data Movement! See why Equifax, Armor & more have joined the “No Movement” Movement!
Are you filtering and trimming data to keep costs down? Are you sacrificing insights because of short retention windows? Are your most talented technical resources bogged down with data prep, movement, and pipeline management? If you answered yes to any of these questions, there is a better way. During this session, Greg Goldsmith (ChaosSearch’s VP of Product Management) and Dave Armlin (VP of Customer Success) will show you how companies like Equifax, Armor, Blackboard and more are activating their cloud object storage as a hot analytical data lake that supports search and SQL analytics at scale – with no data movement or ETL.
This demo will show you how companies like Equifax, Armor, Blackboard and more are:
- Transforming their Amazon S3 and Google Cloud Storage into hot analytical data lakes that supports multiple analytics use cases
- Extending log retention indefinitely at dramatically lower cost
- Empowering their engineers to virtually clean, prep and transform data with no ETL for dynamic data access
- Using their existing analytics and visualization tools such as Kibana, Looker and Tableau to create more and faster insights
- Quickly creating dashboards for data analytics and monitoring
And how you can too!
Session 4: How DataStax Astra DB Enables Rich Customer Experiences Using Real-Time Data at Scale
E-commerce is now at the heart of many businesses invested in enriching the customer experience. Industries include Retail, Finance, Travel, and Media & Entertainment. E-commerce and customer experience investments are driven by customer demand.
A successful e-commerce platform requires some table-stakes services to enable rich customer experiences. These services include product catalog (with real-time inventory management) with filtering and search capabilities, a shopping cart with the ability to save products, wish lists, and apply promo codes, and a payment service to convert the intent to purchase into reality, personalization engines, and social media streams. All these services are instrumental in defining the customer experience, and if done right, can create more revenue opportunities for the business.
During this session, you’ll learn how Astra DB and Astra Streaming can aid enterprises build e-commerce applications at scale without compromise, access data with multi-model flexibility, create real-time data pipelines for analytics in any public cloud (AWS, Azure or GCP). Ravee’s demonstration will be followed by an interactive Q&A.
Session 5: AI-Enabled Advanced Data Lineage: A Strategic Data Imperative for EDM
Enterprise data management as an essential business requirement has emerged as a priority for many organizations. While trust in data is likely the main concern for enterprises, not every tool can provide the same level of certainty and confidence. Data usability is another important factor to consider when applying an EDM system.
Cross-system, multilayered data lineage provides the highest level of certainty to back an enterprise data strategy. Add to that a data catalog with built-in collaboration, and your data and business teams will be set up for data success.
During this presentation, you’ll hear about the following essentials for well-organized, high-performing, and trustworthy enterprise data management, and why they’ve proven critical to our customers:
Automated asset creation: Best practices for building, organizing, and populating data automatically.
Traceability: Being able to visualize data’s journey from source to target, understand where any data asset originated, where and how it’s being used, how any changes to data will have an impact upstream, and so much more.
Built-in Collaboration: In-context communication about data and preserving tribal knowledge about data.