Systems | Development | Analytics | API | Testing

An effective dashboard requires careful design to present data in the best way, and to help more people (users, customers) find insights without feeling overwhelmed. Yellowfin BI comes with a wide variety of chart types as part of its extensive data visualization tools, and while it is tempting to use a lot of eye-catching charts to make a dashboard that looks great, it is important to select the right chart for the right situation.

Yellowfin 9.12 is an extensive release that incorporates a large number of bug fixes, additional data connectors, and customer requested enhancements. The biggest changes in this release focus on Export and Broadcast capabilities. Yellowfin already boasts exceptional reporting capabilities, and 9.12 adds additional features and performance improvements in this area. Yellowfin also has the ability to connect to just about any source of data.

Whether you’re an independent software vendor (ISV) or enterprise-sized company, you want the analytics software you invested in to enhance your users’ decision-making, open up greater access to key data, and improve operational performance for the long-term. However, continuously achieving these business outcomes requires a modern solution. Many organizations still rely on older business intelligence (BI) tools for reporting due to long-term licensing.

The value proposition of embedded analytics in 2024 has never been clearer: real-time insights that help your user base make smarter decisions, while enhancing their engagement with both data analytics as a tool, and your product or business systems. But what about the costs?

From business-wide objectives to long-term targets, every organization has specific metrics they need to track. One way to communicate those insights is a KPI dashboard. Key performance indicator (KPI) dashboards are a great way for executives to improve their management of strategic goals, and keep on top of changes, issues and trends in performance at a high-level, with many useful applications when used correctly, alongside other modern analytics tools.

Imagine transforming raw business data into actionable insights with minimal effort. This is the value proposition of automated analytics, a form of data analytics fast becoming more accessible among modern business intelligence (BI) and analytics software solution vendors. Independent software vendors (ISVs) and enterprise organizations at the cusp of investing in analytics struggle with manual data processes that are time-consuming and prone to errors.

For any product team with a Software as a Service (SaaS) application, the significance of embedding capable, reliable analytics is well understood. But it’s important to remember how valuable these tools are for your users’ experience, too. Having fast access to data and easy ways to explore it is, as you know, key to monitoring business performance, finding trends, sharing insights, and improving your core product. Today’s business user also wants more when they use your product.

Welcome to the latest entry in Yellowfin Japan’s ‘How to?’ blog series! In our previous blog, we created a pie chart that aggregates on the basis of category. By using set analysis, we were able to represent the percentage of Books Only in the numeric display, based on the composition of the items ordered.

For independent software vendors (ISVs), creating unique differentiators and value increasingly entails adopting the latest technologies to enhance your product experience, especially in an ever-evolving competitive landscape with multiple new tech solutions. AI analytics is the latest emerging field in business intelligence (BI) solutions that offers new sophisticated capabilities for the user experience (UX) of your product’s analytics component.

With data continuously growing in complexity and quantity, ensuring data security is more important than ever when choosing to buy a business intelligence (BI) solution. From data protection to data governance, having a BI platform that enables you to control, audit, encrypt and manage user access and usage of sensitive data is essential.