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Dashboards, such as those built using Tableau or PowerBI , provide real-time visualizations that help track key performance indicators (KPIs). Descriptive analytics is a fundamental method that summarizes past data using tools like Excel or SQL to generate reports. Data Scientists require a robust technical foundation.
Business Requirements Analysis and Translation Working with business users to understand their data needs and translate them into technical specifications. DataQuality Assurance Implementing dataquality checks and processes to ensure data accuracy and reliability.
Data Integration and ETL (Extract, Transform, Load) Data Engineers develop and manage data pipelines that extract data from various sources, transform it into a suitable format, and load it into the destination systems. DataQuality and Governance Ensuring dataquality is a critical aspect of a Data Engineer’s role.
BI developer: A BI developer is responsible for designing and implementing BI solutions, including data warehouses, ETL processes, and reports. They may also be involved in data integration and dataquality assurance. They may also be involved in project management and training.
BI developer: A BI developer is responsible for designing and implementing BI solutions, including data warehouses, ETL processes, and reports. They may also be involved in data integration and dataquality assurance. They may also be involved in project management and training.
Because they are the most likely to communicate data insights, they’ll also need to know SQL, and visualization tools such as PowerBI and Tableau as well. Machine Learning Engineer Machine learning engineers will use data much differently than business analysts or data analysts.
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