Systems | Development | Analytics | API | Testing

Can you delete a topic in Apache Kafka? The answer is yes—but the process depends on your Kafka configuration and the environment in which you are working (i.e., if it is self-managed, hosted in the cloud, or a fully managed Kafka service like Confluent Cloud).

AI and analytics are only as powerful as the data they rely on. Without accurate, consistent, and governed data, even the most advanced AI models can produce misleading results. That’s why data quality isn’t just nice to have — it’s essential. At Qlik, our customers across the globe rely on our solutions to drive AI-powered insights, optimize decision-making, and mitigate risk. And it all starts with trusted data.

Snowflake data masking offers a practical and cost-effective solution to mitigate data risk in your non-production Snowflake environments. Enterprises who want to get an even better balance of compliance, quality, and speed add solutions to enhance native Snowflake masking. In this blog, let’s explore how data masking works in Snowflake, how it’s used in various industries, and what you need in a compliance-focused enterprise.

Much of your organization’s most important data is unstructured. Automated data integration allows you to access it, and AI to analyze it.

Data visualization helps people comprehend and attain insight into big data. It represents complex data in visually interesting ways that assist in our understanding, and paves the way for a greater link between the provided raw data, and our overall engagement with it. Nowadays, we accumulate data in ever-increasing sizes. We need an intelligent way to understand vast volumes of information. In analytics, we often use different types of data visualization tools to convey complex data.