There’s no getting around it: selecting the right foundational data-layer components is crucial for long-term application success. That’s why we developed this white paper to give you insights into four key open-source technologies – Apache Cassandra®, Apache Kafka®, Apache Spark™, and OpenSearch® – and how to leverage them for lasting success. Discover everything you’ll want to know about scalable, data-layer technologies: Learn when to choose these technologies and when to avoid them Explore h

IT leaders are experiencing rapid evolution in AI amid sustained investment uncertainty. As AI evolves, enhanced cybersecurity and hiring challenges grow. This whitepaper offers real strategies to manage risks and position your organization for success.

Entity Resolution Sometimes referred to as data matching or fuzzy matching, entity resolution, is critical for data quality, analytics, graph visualization and AI. Learn what entity resolution is, why it matters, how it works and its benefits. Advanced entity resolution using AI is crucial because it efficiently and easily solves many of today’s data quality and analytics problems.

In the fast-moving manufacturing sector, delivering mission-critical data insights to empower your end users or customers can be a challenge. Traditional BI tools can be cumbersome and difficult to integrate - but it doesn't have to be this way. Logi Symphony offers a powerful and user-friendly solution, allowing you to seamlessly embed self-service analytics, generative AI, data visualization, and pixel-perfect reporting directly into your applications.

With its unparalleled flexibility, rapid development and cost-saving capabilities, open source is proving time and again that it’s the leader in data management. But as the growth in open source adoption increases, so does the complexity of your data infrastructure. In this Analyst Brief developed with IDC, discover how and why the best solution to this complexity is a managed service, including: Streamlined compliance with some of the most complex regulatory guidelines Simplified operations, li

In the rapidly evolving healthcare industry, delivering data insights to end users or customers can be a significant challenge for product managers, product owners, and application team developers. The complexity of healthcare data, the need for real-time analytics, and the demand for user-friendly interfaces can often seem overwhelming. But with Logi Symphony, these challenges become opportunities.

Adding high-quality entity resolution capabilities to enterprise applications, services, data fabrics or data pipelines can be daunting and expensive. Organizations often invest millions of dollars and years of effort to achieve subpar results. This guide will walk you through the requirements and challenges of implementing entity resolution. By the end, you'll understand what to look for, the most common mistakes and pitfalls to avoid, and your options.

The complexity of financial data, the need for real-time insight, and the demand for user-friendly visualizations can seem daunting when it comes to analytics - but there is an easier way. With Logi Symphony, we aim to turn these challenges into opportunities. Our platform empowers you to seamlessly integrate advanced data analytics, generative AI, data visualization, and pixel-perfect reporting into your applications, transforming raw data into actionable insights.

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.

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.

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.

Organizations look to embedded analytics to provide greater self-service for users, introduce AI capabilities, offer better insight into data, and provide customizable dashboards that present data in a visually pleasing, easy-to-access format. To better understand the factors behind the decision to build or buy analytics, insightsoftware partnered with Hanover Research to survey IT, software development, and analytics professionals on why they make the embedded analytics choices they do.

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.

In the rapidly-evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your application’s analytics capabilities? Imagine having an AI tool that answers your user’s questions with a deep understanding of the context in their business and applications, nuances of their industry, and unique challenges they face.

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.

Are you thinking of adding enhanced data matching and relationship detection to your product or service? Do you need to know more about what to look for when assessing your options? The Senzing Entity Resolution Buyer’s Guide gives you step-by-step details about everything you should consider when evaluating entity resolution technologies. You’ll learn about use cases, technology and deployment options, top ten evaluation criteria and more.

While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?