Artificial Intelligence and the tools generated from it have been increasing in popularity. This growth in popularity has, unfortunately, led to some behind their creations to scientists, have fallen to the wayside in public view. While AI tools can only function effectively with the right data and algorithms, data scientists are responsible for preparing and organising data, selecting and optimising algorithms, and interpreting the results of AI\u00a0models.<\/p>\n
While there are many roles in the data industry that people can do John Alex<\/a> says that their roles can be separated into two primary\u00a0groups:<\/p>\n Data engineers are in charge of gathering data, processing it through various procedures, including data cleansing, and then storing it so that it is in a form that is suitable for future analysis.Data scientists do the most difficult portion. Data scientists develop models and do exploratory analysis on the data that data engineers have generated to find multiple\u00a0answers.<\/p>\n Emidio Amadebai<\/a> claims that as technology continues to advance, there are certain roles in the data engineering field that are expected to be automated in the future including:<\/p>\n Collecting the data from various sources and combining them.Cleaning and delivering the data to the places where it\u2019s\u00a0needed.Deploying the models automatically once they\u2019re\u00a0ready.Detecting certain trends in\u00a0data.Generating variations of certain\u00a0models.<\/p>\n However, it\u2019s important to note that automation doesn\u2019t eliminate the need for data engineers altogether. As they will be needed\u00a0for:<\/p>\n Supporting data while keeping it optimisedComing up with non-SQL pipelinesManaging the core infrastructure of\u00a0data<\/p>\n While artificial intelligence has made significant advancements to automate various tasks in the data engineering field. There are some tasks that cannot be completely replace data engineers, such\u00a0as<\/a>:<\/p>\n Listening to clients\u2019 needs, translate those needs into models, and implement them in a meaningful wayPeople can adapt to multiple different scenarios at\u00a0onceAI can only solve issues that they have been trained to solve while people can adapt to new scenariosPeople have an intuition of the real world that AI\u00a0lack<\/p>\n Just as computers did not take people\u2019s jobs but instead elevated people to be able to perform better, AI will have the same effect on the data industry\u00a0by:<\/p>\n Saving time from the boring\u00a0tasksAI can help identifying tiny\u00a0patternsAI can help people have a more accurate\u00a0outcome<\/p>\n AI tools are powerful, but they still require human expertise to ensure that the insights generated are accurate and relevant to the business. In short, data engineers and data scientists play a critical role in the successful implementation of AI and machine learning in organisations. We at Eden AI will like to help you get the full capabilities of your AI tools so come and contact us @helloword@edenai.co.za<\/a>.<\/p>\n This article was enriched by the following references:<\/p>\n John Alex (2022) Nascom Insight Community Will Artificial Intelligence (AI) Replace Data Science In The Future? https:\/\/community.nasscom.in\/communities\/data-science-ai-community\/will-artificial-intelligence-ai-replace-data-science-future<\/a><\/p>\n Emidio Amadebai Will AI Replace Data Science https:\/\/www.analyticsfordecisions.com\/will-ai-replace-data-science\/<\/a><\/p>\n Robert de Graaf (2019) Data Scientists Can\u2019t Be Replaced By AI https:\/\/towardsdatascience.com\/data-scientists-cant-be-replaced-by-ai-841a0a2a8df9<\/a><\/p>\n \u200bStories by Eden AI on Medium\u00a0\u00a0<\/p>\nThe capabilities of Artificial Intelligence<\/h3>\n
Why Artificial intelligence cannot replace data scientists<\/h3>\n