Systems | Development | Analytics | API | Testing

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Introducing Qlik's AI Accelerator - Delivering Tangible Customer Outcomes in Generative AI Integration

At Qlik, we're witnessing a thrilling shift in the landscape of data analysis, customer engagement, and decision-making processes, all thanks to the advent of generative AI, especially Large Language Models (LLMs). The potential for transformation across all sectors is enormous, but the journey toward integration can be daunting for many businesses with many leaders wondering where to start in integrating the exciting capabilities of AI into their daily workflows.

Using DreamFactory for Legacy Application Modernization

Many organizations face the challenge of legacy application modernization. DreamFactory, an on-premise API generation and management platform, offers a robust solution for this transition. By enabling the creation of APIs from any data source, automating integration processes, and enhancing security measures, DreamFactory simplifies the modernization of outdated systems.

Event-Driven Architecture (EDA) vs Request/Response (RR)

In this video, Adam Bellemare compares and contrasts Event-Driven and Request-Driven Architectures to give you a better idea of the tradeoffs and benefits involved with each. Many developers start in the synchronous request-response (RR) world, using REST and RPC to build inter-service communications. But tight service-to-service coupling, scalability, fan-out sensitivity, and data access issues can still remain.

Basel 3.1: Strengthening Global Financial Framework

The financial crisis of 2008 exposed vulnerabilities in the global banking system. In response, the Basel Committee on Banking Supervision (BCBS) introduced the Basel III reforms, a set of regulations designed to strengthen banks’ capital adequacy and risk management practices. Basel 3.1, the latest iteration of these reforms, is set to be implemented in major jurisdictions like the EU and UK in 2025.

How Snowflake Powers The Next Generation Of Cybersecurity Applications

Cybersecurity is extremely data-intensive and complex. Top cybersecurity companies such as Lacework, Sophos, Panther, Hunters, Auditboard, Orca Security, and Dassana leverage Snowflake to provide out-of-the-box solutions. These companies are building the next generation of cybersecurity applications by harnessing the power of the Snowflake Data Cloud to provide differentiated product capabilities to security teams.

Kafka-docker-composer: A Simple Tool to Create a docker-compose.yml File for Failover Testing

Confluent has published official Docker containers for many years. They are the basis for deploying a cluster in Kubernetes using Confluent for Kubernetes (CFK), and one of the underpinning technologies behind Confluent Cloud. For testing, containers are convenient for quickly spinning up a local cluster with all the components required, such as Confluent Schema Registry or Confluent Control Center.

Data Governance Framework: What is it? Importance, Pillars and Best Practices

Data forms the foundation of the modern insurance industry, where every operation relies on digitized systems, including risk assessment, policy underwriting, customer service, and regulatory compliance. Given this reliance, insurance companies must process and manage data effectively to gain valuable insight, mitigate risks, and streamline operations.

Decoding the Dynamics of Software Development Team Structure

In the realm of software development, success isn't merely about the lines of code; it's about the people behind them and how they collaborate. The structure of a software development team lays the foundation for efficient communication, effective problem-solving, and ultimately, the delivery of high-quality products. In this exploration, we delve into the intricate layers of software development team structures, uncovering the roles, methodologies, and strategies that drive innovation and productivity.

Confluent Connectors | Fast, frictionless, and secure Apache Kafka integrations

Every company faces the perennial problem of data integration but often experiences data silos, data quality issues, and data loss from point-to-point, batch-based integrations. Connectors decouple data sources and sinks through Apache Kafka, simplifying your architecture while providing flexibility, resiliency, and reliability at a massive scale.