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

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.

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.

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.

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.

If you’re considering migrating from DataStax Enterprise (DSE) to open source Apache Cassandra®, our comprehensive guide is tailored for architects, engineers, and IT directors. Whether you’re motivated by cost savings, avoiding vendor lock-in, or embracing the vibrant open-source community, Apache Cassandra offers robust value. Transition seamlessly to Instaclustr Managed Cassandra with our expert insights, ensuring zero downtime during migration.

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.

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.

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.

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.

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?

Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

Just by embedding analytics, app owners can charge 24% more for their product. How much value could you add? This framework from Software Pricing Partners explains how application enhancements can extend your product offerings. You’ll learn: How to take a disciplined approach to pricing The three elements of the Packaging Decision Framework Ways to structure your new embedded analytics offering Download the White Paper to learn about How To Package & Price Embedded Analytics.

The possibilities for embedded analytics to drive real value for businesses, end users, and society are as fascinating as they are limitless. No matter the industry, brand after brand is finding that analytics can be the solution to a multitude of business challenges. Go deep with five insightsoftware customers as they share the details of their analytics journeys and discuss the transformative power of data.