The Rise of Data Wrangling and What It Means for Data Analysis
Consequently, the emergence of IoT and sophisticated data collection models ensure that there are no boundaries to the types or amounts of data an organization can procure. While collected data forms the foundation, the crucial step of analyzing this data effectively to derive actionable insights is made possible with data wrangling solutions.
Helping data analysts to make better sense of vast, diverse and clumsy data sets, data wrangling is the first piece of the data analysis puzzle. Data can then be examined much faster and more effectively as data wrangling cleans and unifies complex data, enabling enterprises to understand their data better. Data wrangling would typically involve manually converting data from its original format into easily digestible parts using tools like visualization and aggregation. But, data wrangling solutions can drastically improve the process facilitating better data analytics as a result.
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