Blog
Why Is Data-Driven Analytics Of Interest To Companies?
Data-driven analytics is becoming increasingly important for companies as they seek to gain insights that can drive their decision-making processes in today’s dynamic landscape. With more data being collected than ever, data analytics promises to help more organisations uncover patterns and trends that they can exploit to improve their business operations and profitability. The article aims to explore the importance
Essential Elements of Data Storytelling
Data analytics are not enough to motivate an entire team or organisation to utilise and derive value from it. However, a compelling narrative, characters, a setting, a problem, and a solution, may inspire teams to make the most of analytics applications. Here enters data storytelling! Data storytelling is the art of communicating insights from data analysis in a compelling, easily
What is Data Storytelling?
According to researchers, colour visuals increase a human’s willingness to read by 80%. Furthermore, data visualisations are known to help an individual’s ability to interpret data faster, recognise patterns and find exceptions, in a fun and efficient way. And with the proliferation of data in our daily social lives, data literacy is becoming more crucial for making sense of intricate
Visual Analytics: How to Use Data to Drive Decisions
Most businesses have data they’d like to exploit to make mission-critical decisions, and perform analytic functions. When dealing with large amounts of information, achieving data-driven outcomes with repeatability and at scale can be exceedingly challenging. The process becomes incredibly computationally intensive and time-consuming. What if there was a better way? Well, this is where visual analytics comes into play. What
What Is Data Visualisation and Why Is It Important?
Data visualisation is a process that fosters new innovation and discovery through the graphical representation of data. It revolves around presenting data in a manner that makes it easier for one’s audience to understand and dissect. This data science discipline is known to aid in decision support and help enterprises control their data in an effective manner and convert it