Events & Webinars

2023 Modern Data Architecture Trends: New Market Research and Guidance

To shed light on the adoption and maturity of trending data architectures, Unisphere Research and DBTA joined forces with Radiant Advisors to launch an inaugural study on modern data architecture trends. Kinetica’s Chad Meley joins DBTA and Radiant Advisors for a lively discussion about the survey results on how organizations are evaluating these trends, including the potential business value and challenges of each and key drivers for adoption. You’ll hear the latest market research, and real-world experiences for a deeper understanding of modern data architecture strategies to better navigate this evolving space. Speakers

ACAMS Assembly USA 2023

Accelerating Data-Powered Disaster Response for Utilities with Disaster Technologies and Kinetica

MEET THE HOSTS: Sean Griffin, CEO, Disaster Tech & Samm DiStasio, VP of Business Development, Kinetica Utilities are constantly dealing with threats and hazards, including hurricanes and wildfires, that disrupt service, threaten citizen safety, and incur significant damages. For emergency managers tasked with preparing for disasters as well as coordinating swift disaster response, leveraging data and analytics to enhance operational workflows is critical. In this Tech Talk, we’ll share how Disaster Tech has developed an innovative platform to help emergency managers and utilities analyze and visualize data at massive scale and high performance to optimize disaster response and accelerate time to restoring services. IN THIS TECH TALK WE’LL DISCUSS: How Disaster Tech, Kinetica, and NVIDIA, partner to offer a “single pane of glass for data and analytics” for emergency managers at utilities How the Disaster Tech platform helps utilities to better serve their communities and while also saving time, money, and lives Example applications of the Disaster Tech platform for utilities where new capabilities are unlocked through the […]

Active Analytics for Dynamic Inventory Replenishment

For retailers, ensuring products are always in stock is a top priority. However, with the complexity of the modern supply chain and the sheer number of SKUs involved, this is a significant logistical challenge. In this webinar learn how Kinetica works with one of the world’s largest retailers to power dynamic inventory replenishment.

Amazon Redshift: Expectations vs Reality & How to Lower Your TCO

Hosted by: Mathew Hawkins, Sr. Director of Solutions Engineering, Kinetica Migrating from Redshift to Kinetica has never been easier and offers better performance and lower TCO. Kinetica’s Streaming Data Warehouse integrates with Kinesis and S3 to enable distributed analytics on your full data corpus. With GPU acceleration and vectorized processing, Kinetica delivers up to 8x more performance on like-for-like infrastructure, allowing for cost reduction while maintaining SLAs. DURING THIS TALK WE WILL COVER: Kinetica’s ease of use How to get faster analytics and at lower cost than Redshift A demonstration on how Kinetica analyzes streaming, historical and geospatial data in real-time Connecting to Kinesis and loading data from S3 TCO comparison and product feature comparison

An Introduction to Graph Analytics With The Kinetica Streaming Data Warehouse

MEET THE HOST: Genie Yuan, Senior Director – Customer Success, Kinetica The Kinetica Streaming Data Warehouse gives organizations up-to-the-second results that incorporate all their data in a powerful, unified data warehouse. In this Tech Talk, we’ll discuss Kinetica’s unique ability to combine graph analytics with historical, streaming, location analytics and machine learning. Kinetica enables organizations to simplify their infrastructure on a single platform and eliminate data movement, and costly integration with additional graph solutions. As a result, Kinetica can power transformational enterprise use cases such as vehicle routing, matching supply and demand, and fraud detection that take advantage of built in graph solvers and powerful querying capabilities along with real-time streaming data, geospatial analysis, and predictive models. IN THIS TECH TALK WE WILL COVER: An introduction to graph analytics The value of converging graph analytics with streaming, historical, and location analytics as well as machine learning with Kinetica Real-world use cases and non-traditional applications of graph analytics A demo of Kinetica’s converged graph capabilities

Analyzing Sensor Data in Real-Time

The volume of sensor data being generated is rapidly increasing. This data can be used to gain valuable insights into various systems, such as monitoring the health of industrial equipment, tracking the movement of vehicles, and detecting patterns in financial transactions. However, the opportunities are often perishable necessitating that the data be analyzed and acted on in real-time. In this webinar, Insights Industry Editor Joe McKendrick and Kinetica President Amit Vij discuss: Various techniques and technologies used for real-time analysis of sensor data, including data streaming, time series analysis, spatial analysis, and machine learning. Common use cases for real-time sensor data analysis, including asset tracking, telco network optimization, and real-time trading.

Automate the Boring Stuff with User Defined Functions: Enhancing Performance for Analytics at Scale

MEET THE HOSTS: Dave Rench McCauley, Solutions Architect, Kinetica & Zhe Wu, Professional Services, Kinetica In this Tech Talk we’ll discuss combining the optimization benefits of SQL with the flexibility of a procedural language. By using User Defined Functions (UDFs) with the Kinetica Streaming Data Warehouse, developers, analysts, and others can automate processes like ETL, common analytical tasks, and data re-labeling to improve performance, especially when working with massive datasets. We’ll discuss what’s unique about Kinetica’s UDF functionality and how it fits into the context of other popular UDF implementations, in addition to providing a demo of Kinetica’s capabilities in this arena. IN THIS TECH TALK WE’LL COVER: The value of User Defined Functions Spark/Hive vs. SQL vs. Kinetica – benefits of each for UDF An overview of UDFs in Kinetica Distributed vs. non-distributed UDFs Real-world use cases for UDFs Demo

AWS Reinvent

Beyond BI: How CDOs Can Transform Their Organizations With Active Analytics l June 3

Beyond BI: How CDOs Can Transform Their Organizations With Active Analytics

MEET THE HOSTS: Vira Shanty, CEO and Founder, Frontera Consulting & formerly CDO, OVO & Lippo Group With our society, governments and enterprises in the midst of digital transformation, opportunities to benefit from this torrent of data abound. Yet, many organizations are struggling with how to monetize this new data, and are limited by old “BI” mindsets. Our topic in this session is “CDO tech”, how Chief Data Officers can help their companies shift their analytics practices to realize new opportunities of digital transformation. We’ll be joined by Vira Shanty, CEO and Founder at Frontera Consulting, and previously Chief Data Officer at OVO, the leading digital payments platform of Indonesia. While Vira was at OVO, they received multiple international digital and data awards for their innovation. Prior to joining OVO, she worked for Telkomsel, the largest mobile telecommunications organization in Indonesia and led their data analytics team. IN THIS TALK WE’LL COVER: How digital transformation has changed organizational data and analytics A methodology for finding new analytics opportunities beyond […]

Beyond Text: Creating GenAI Apps that Leverage All Your Data for Deeper Insights

Struggling to get actionable insights from all your data? Join Kinetica’s CEO and co-founder, Nima Negahban, to explore how you can go beyond basic conversational search to unlock deeper insights with GenAI. In this webinar, Nima will showcase a GenAI application powered by Kinetica that retrieves insights from both text and tabular data, delivering more contextually accurate answers. Discover how Kinetica’s unique Language to SQL and Data Cataloging features enable multimodal retrieval, combining vector search on embeddings with traditional SQL queries on relational tables. With Kinetica’s accelerated query engine, you can execute complex queries against real-time data in seconds, providing your LLMs with the additional context needed to answer user questions effectively. Kinetica’s enterprise-grade database also offers robust security features, including row and column-level access controls, ensuring that sensitive data remains protected and accessible only to authorized users. Learn how to harness the full potential of your data—text and tabular—to build sophisticated GenAI apps that provide meaningful, secure insights.

Bring Your Own Stream: Deploying Algorithms Closer to Data for Real-time Analysis

Learn about the value of the Kinetica Streaming Data Warehouse in this webinar on Thursday, December 10th at 2 p.m. Register now. The growth of streaming data sources is driving the need for real-time geospatial, graph analytics, and machine learning capabilities at scale. These high velocity use cases require a streaming data warehouse, a platform delivering up-to-the-second analysis on data as it arrives. During this webinar, learn about how the Kinetica Streaming Data Warehouse is suited for real-time analysis and high-velocity, high-scale use cases. Register Now Learning objectives: Best practices for developing a system architecture for a streaming data warehouse Integrated model training with NVIDIA RAPIDS Autonomous Kubernetes orchestration Comprehensive model auditing Accelerated geospatial and graph analytics at scale using the raw processing power of the NVIDIA GPU Example implementations from our work with federal clients, including the Department of State and the U.S. Postal Service, where we optimize routes in real-time for carriers and 250,000+ vehicles Hosted By:

Bring Your Own Stream: Deploying Algorithms Closer to Data for Real-Time Analysis

MEET THE HOSTS: Nima Negahban – Founder & CTO – Kinetica, Tim Barr – Director, Federal Solution Engineering – Kinetica The growth of streaming data sources is driving the need for real-time geospatial, graph analytics, and machine learning capabilities at scale. These high velocity use cases require a streaming data warehouse, a platform delivering up-to-the-second analysis on data as it arrives. Learn why legacy systems won’t hold up and why the Kinetica Streaming Data Warehouse is suited for real-time analysis and high-velocity, high-scale use cases. DURING THIS WEBINAR WE WILL COVER: Best practices for developing a system architecture for a streaming data warehouse Integrated model training with NVIDIA RAPIDS Autonomous Kubernetes orchestration Comprehensive model auditing Accelerated geospatial and graph analytics at scale using the raw processing power of the NVIDIA GPU Example implementations from our work with federal clients, including the Department of State and the U.S. Postal Service, where we optimize routes in real-time for carriers and 250,000+ vehicles

Building Real-Time Location Intelligence Apps

The ability to track and analyze location data in real time has become increasingly important for businesses and organizations across various industries. Whether it’s to optimize delivery routes, monitor fleet vehicles, or track assets, real-time location intelligence apps have become essential tools for decision-making and business operations. In this webinar, we will: Explore the fundamentals of building real-time location intelligence apps, including key enabling technologies like spatio-temporal databases and real-time data streaming. Dive into the key features and functionalities that are crucial for real-time location intelligence apps, such as real-time tracking, geofencing, and event triggering. Cover the best practices and strategies for designing and implementing real-time location intelligence apps, including scalability and performance optimization in the cloud

CDAO Europe – Digital Event

COVID-19 and Supply Chain Agility: How a Streaming Data Warehouse Keeps You Always On-Time and Fully Stocked

Hosted by: Matt Brown, Product Manager, Kinetica & Amit Kesarwani, Principal Solutions Engineer, Kinetica The supply chain and logistics ecosystem faces more complexities than ever before with drastic fluctuations in supply and demand. With modern tools, you can harness the wealth of data available today to respond with in the moment, data-driven decisions. In this talk we will show how Kinetica seamlessly brings together relational, graph and ML analytics on streaming data to solve supply chain and logistic use cases. DURING THIS TALK WE WILL COVER: How real-time analytics can be applied predictively, or post-mortem Deploying a predictive model in Kinetica for demand forecasting Leveraging streaming data to gain real-time visibility into your supply chain Using graph solvers to execute route optimization and exception management Applying powerful visualization and geospatial analytics for fleet management

Data Driven Planning to Make Cities Smarter, an End-to-End IoT Example

MEET THE HOSTS: Antonio Cotroneo, Sr. Solution Engineer, Emerging Analytics, Kinetica  /  Nohyun Myung, Director, Emerging Analytics, Kinetica This demo-driven session explores a smart city use case with Kinetica that blends location data, stream processing, and historical analytics into a custom application. We’ll show an active analytical app where real-time GPS data from local vehicles is monitored, visualized, and analyzed. IN THIS SESSION WE’LL DEMONSTRATE HOW TO: Stream high volumes of dynamic GPS observations Perform historical data exploration Conduct a scenario planning study using native graph and geospatial analytical capabilities