Analytics

It sounds counterintuitive—using a technology that has trust issues to create more trustworthy data. But smart engineers can put generative AI to work to improve the quality of their data, allowing them to build more accurate and trustworthy AI-powered applications.

In today's data-driven business landscape, the ability to predict trends, explain drivers, and act on insights is no longer a luxury—it's a necessity. Yet for many organizations, the path from data to predictive intelligence remains challenging. Data science resources are scarce, and traditional tools often require specialized expertise that most analytics teams lack. At Qlik, we believe that the power of predictive analytics should be accessible to all.

Learn how we prioritize privacy and data protection with a robust framework that adheres to the GDPR and other global regulations.

Imagine a multinational business that deals with multiple suppliers and customers scattered across the globe, each with their own systems and processes. How does it ensure smooth communication and transactions with its business partners? The answer is Electronic Data Interchange (EDI), a standardized method for exchanging electronic documents between businesses.

I’m excited to announce that Confluent has acquired WarpStream, an innovative Kafka-compatible streaming solution with a unique architecture. We’re excited to be adding their product to our portfolio alongside Confluent Platform and Confluent Cloud to serve customers who want a cloud-native streaming offering in their own cloud account.

Oracle SQL Developer is a powerful tool widely used by data professionals for managing and interacting with Oracle databases. One of the common tasks that data analysts in mid-market companies frequently encounter is the need to export data from Oracle SQL Developer to Excel for further analysis, reporting, or sharing. This blog will provide a detailed, step-by-step guide on how to achieve this, ensuring that every method is covered comprehensively, catering to various user needs and preferences.

Data elements are the fundamental building blocks of EDI documents. They represent individual information within a transaction set, such as city, state, country, item number, quantity, and price. Each data element is defined by its data type, which specifies whether it’s numeric, alphanumeric, a date, or a time. Additionally, the definition includes details like minimum and maximum length requirements and any applicable code values.

What is data fabric architecture? The case for data fabric 4 key facts about data fabric architecture Data fabric architecture can modernize and future-proof your data approach Data fabric architecture is a virtual data layer that connects any number of external systems together to provide unified access and a complete, 360-degree view of an organization’s data. Whether your data lives in legacy systems or multi-cloud environments, a data fabric can connect these systems together for a unified view.