Charting libraries are in great demand, and their creation and use are becoming increasingly popular in languages such as JavaScript. As evidence, several JavaScript charting libraries are available, both commercial and open-source, with a wide range of functionalities to meet the demands of users. But how can a developer make an informed decision and choose the best JavaScript charting library? It's a difficult question, but we're here to assist!

Introduced in 9.7 as the simplest way to ask questions of your data, Yellowfin 9.8 delivers exciting updates to Guided NLQ, and additional improvements to our report builder. The latest release makes Guided NLQ even more powerful and simpler to use, with new question types (Cross-tab), more intuitive questions with field synonyms and default date periods, and protection against long-running queries - in addition to faster report building.

Data visualization is an elementary component of human learning and understanding. It's also a significant capability of business intelligence (BI) and analytics solutions today. So, how did data visualization first come to be? The humble origins and gradual evolution of data visualization has led to an interesting timeline.

A business intelligence (BI) dashboard is an essential tool for managing and monitoring your business data. Well-designed BI dashboards can help you quickly and easily understand your company’s performance, identify trends, and make informed decisions. In this article, we will discuss seven key elements of an effective business intelligence dashboard. By understanding these elements, you can create a powerful tool that helps you manage your business data effectively.

Data visualization is one of the most important capabilities of any business intelligence (BI) and analytics solution. It helps people translate complex data into a visual context, like a chart or a graph, identify trends numbers alone can't easily reveal, and discover hidden patterns in your dashboard. Data visualization also provides a wealth of additional benefits, such as enabling easier understanding of the correlation between operations and results.

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, so we need an intelligent way to understand such vast volumes of information. In analytics, we often use different types of data visualization to convey complex datasets.

Dashboards are an important data analytics tool for understanding business metrics and managing your business performance. However, if your dashboard is not designed well, it can be difficult to use for analysis, and ineffective for decision-making. Dashboard design should be simple and accessible, and reflect your company's branding and identity. Ensuring your analytical dashboard is readable, usable and accurate is heavily reliant on following best practice dashboard design.

Technology is always evolving, and so is the way we use it to collect and analyze data. From humble spreadsheet beginnings to fully automated business monitoring and AI-powered analysis, the range of analytics tools on offer today is astounding to consider. The business intelligence dashboard is one such option. It has existed for decades as a tool for organizations to monitor and analyze operational data - and it's not quite dead yet.