The newest release of DataClarity is here! DataClarity 2020.2 is packed with innovative features and improved capabilities over previous versions. Let’s take a look at our latest release. Data Preparation Reuse uploaded files to create multiple datasets Now, users can reuse uploaded files as saved connections when creating new datasets. When a file is uploaded [...]
The newest release of DataClarity is here! With DataClarity 2020.1, we’re continuing to make it easier for you to connect, prepare, and visualize your data. This release is packed with amazing features and ideas from our loyal customers. Here are a few of our favorites: Advanced dataset sharing permissions, including view, share, edit, and [...]
Did you know that data preparation is considered one of the most important and time-consuming steps in data exploration and analysis? If you could spend some time for proper planning of this process in the very beginning, it can save you time later and help get the relevant insights. Data preparation is the process [...]
Creating a Data Science Culture Virtually all organizations today are searching for new methods to extract more usable information from the vast amounts of data being amassed from an ever-growing number of enterprise systems, applications, and tools. In this quest to drive analytics maturity and modern data-driven decision-making, businesses must evolve from their traditional [...]
Nowadays, the importance of location data continues to grow as businesses expand and spread over various geographical areas. Consequently, geospatial analysis becomes a basic necessity as it helps us discover patterns correlating with geographic locations. When choosing the best map visualization for plotting geographical data, we need to consider the specifics of each business [...]
Your data is geographically distributed, and you want to visualize at least two metrics in your data? The pointer map might be a good choice. The pointer map, also known as a “bubble map” or “symbol map”, has markers placed over geographical locations. Pointer maps can show two quantitative values — one by varying [...]
What’s a logarithmic scale? That’s a commonly asked question by storyboard designers. Let’s uncover its true power by seeing when and how the logarithmic scale is applied based on examples from DataClarity visualizations. The reason to use logarithmic scales is to resolve an issue with visualizations that skew towards large values in a dataset. [...]
