The consequences of businesses who do not perform data quality assessments can be devastating to business growth. Poor data quality can lead to executing the wrong business strategies, reduced efficiency, increased financial costs, damaged customer relationships and ultimately to bankruptcy. Therefore, in the third part of the free pdf course notes on data literacy, we provide information on how to read data, by distinguishing between good and bad data, what are the negative impacts of poor data quality, and the various descriptive methods that characterize a dataset.
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Who is it for
This data literacy study guide is for aspiring data scientists, business analysts, data engineers, and anyone who is looking to learn in-demand data skills that are going to set them on the track of a future-proof career. Designed to build a solid foundation in the data language, this resource will put you on the track to success.
How it can help you
Studying the data literacy lecture notes will give you the big picture understanding of the role that data plays in the modern global workplace and provide you with the analytical tools to outcompete data illiterate peers and execute data strategies that are the driving force behind business growth and success.
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