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They are often unable to handle large, diverse data sets from multiple sources. Another issue is ensuring dataquality through cleansing processes to remove errors and standardize formats. Staffing teams with skilled data scientists and AI specialists is difficult, given the severe global shortage of talent.
And shows how big data and the advances in analyticaltechnologies are shaping the way the world is perceived. 2) Designing Data-Intensive Applications by Martin Kleppman. Topics covered here range from backtesting and benchmarking approaches to dataquality issues, software tools, and model documentation practices.
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