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About Anna Korolivska

Anna Korolivska, a Product Specialist at DataClarity, is a member of the global platform owner team who performs client use case, market, technology and competitive research and analysis to drive road map innovation in the areas of data virtualization, data visualization, and data science.

Fostering a Data Science Culture Throughout Your Organization

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 [...]

Filled Map – a key visualization in geospatial analysis

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 [...]

Get the most out of Pointer Maps

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 [...]

The Power of Logarithmic Scale

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. [...]

Prepare for Data Preparation

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 [...]