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Data scientists and data analysts often end up spending a lot of time doing mundane tasks like cleansing, shaping and preparing data. Typically, these tasks are roadblocks for starting the more enjoyable part of their work – analyzing their datasets or building and training machine learning models – because datasets typically are not in a format that can be readily consumed. They first need to be cleansed and refined before they are fit for analysis.
IBM Data Refinery addresses this issue and simplifies the tasks of refining data and its workflows. It provides an intuitive, self-service data preparation environment where you can quickly analyze, cleanse and prepare data sets.
In this webcast, we will use Kaggle datasets to turn raw data into AI-ready data during a live demonstration. You can build skills in working with and cleansing, shaping and preparing numeric, text and time series data. Then we’ll leave plenty of time for you to ask the experts your questions regarding your own data prep challenges and learn how Watson Studio Desktop can help.
We’ll be working within Watson Studio Desktop, so if you don’t already have the software, sign up for a free trial here.