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It’s no surprise that Apache Cassandra has emerged as a popular choice for organizations of all sizes seeking a powerful solution to manage their data at a scale—but with great power comes great responsibility. Due to the inherent complexity of distributed databases, this white paper will uncover the 10 rules you’ll want to know when managing Apache Cassandra.
Executive leaders and board members are pushing their teams to adopt Generative AI to gain a competitive edge, save money, and otherwise take advantage of the promise of this new era of artificial intelligence. There's no question that it is challenging to figure out where to focus and how to advance when it’s a new field that is evolving everyday. 💡 This new webinar featuring Maher Hanafi, VP of Engineering at Betterworks, will explore a practical framework to transform Generative AI pr
With no barriers to entry you can get started with Snowflake for next to nothing, but as you may already know, costs can quickly spiral out of control. While usage costs can be better managed for your internal BI use case, Snowflake costs skyrocket for SaaS providers because the need to deliver real-time, interactive analytics in a multi-tenant environment is always on.
Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.
Without proper guidance, it’s easy to miss out on Kafka’s full capabilities. While not the easiest technology to optimize, Kafka rewards those willing to explore its depths. Under the hood, it is an elegant system for stream processing, event sourcing, and data integration. Download this white paper to learn the 10 critical rules that will help you optimize your Kafka system and unlock its full potential.
Multi-tenant architecture allows software vendors to realize tremendous efficiencies by maintaining a single application stack instead of separate database instances while meeting data privacy needs. When you use a data warehouse to power your multi-tenant analytics, the proper approach is vital. Multi-tenant analytics is NOT the primary use case with traditional data warehouses, causing data security challenges.
“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.
Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.
Apache Cassandra is an open-source distributed database that boasts an architecture that delivers high scalability, near 100% availability, and powerful read-and-write performance required for many data-heavy use cases. However, many developers and administrators who are new to this NoSQL database often encounter several challenges that can impact its performance.
Join our exclusive webinar with top industry visionaries, where we'll explore the latest innovations in Artificial Intelligence and the incredible potential of LLMs. We'll walk through two compelling case studies that showcase how AI is reimagining industries and revolutionizing the way we interact with technology. Some takeaways include: How to test and evaluate results 📊 Why confidence scoring matters 🔐 How to assess cost and quality 🤖 Cross-platform cost vs. quality tr
As a SaaS leader, you know that the more metrics, insights, and analytics you add to your products, the more engagement you’ll have – and the stickier your product will become with customers. At what point do you decide to keep building your analytics in-house or invest in an embedded analytics solution? Read our Build vs. Buy Analytics guide to learn: Top 4 benefits of embedded analytics A quick cost comparison of in-house analytics development vs embedded analytics 10 considerations to help yo
Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs. Putting the right LLMOps process in place today will pay dividends tomorrow, enabling you to leverage the part of AI that constitutes your IP – your data – to build a defensible AI strategy fo
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