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Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create datapipelines, ETL processes, and databases to facilitate smooth data flow and storage. Big Data Processing: Apache Hadoop, Apache Spark, etc.
Generative AI can be used to automate the datamodeling process by generating entity-relationship diagrams or other types of datamodels and assist in UI design process by generating wireframes or high-fidelity mockups. GPT-4 DataPipelines: Transform JSON to SQL Schema Instantly Blockstream’s public Bitcoin API.
Data scientists frame the business problem and the objective into a statistical solution and start with the very first step of data exploration. EDA, as it is popularly called, is the pivotal phase of the project where discoveries are made. Approvals from stakeholders ML projects are inherently iterative by nature.
Its less about just building models and more about how those models fit into scalable, business-critical systems usually in the cloud. The role of a data scientist is changing so fast that often schools cant keep up. Universities still mostly focus on things like EDA, data cleaning, and building/fine-tune models.
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