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Data Scientist Job Description – What Companies Look For in 2025

Pickl AI

Visualization and Reporting: Creating dashboards and reports using tools like Tableau or Power BI to communicate insights effectively to non-technical stakeholders, including management and clients. Data Visualization: Ability to create intuitive visualizations using Matplotlib, Seaborn, Tableau, or Power BI to convey insights clearly.

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Business Analytics vs Data Science: Which One Is Right for You?

Pickl AI

Dashboards, such as those built using Tableau or Power BI , provide real-time visualizations that help track key performance indicators (KPIs). Big data platforms such as Apache Hadoop and Spark help handle massive datasets efficiently. Data Scientists require a robust technical foundation.

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What is Data-driven vs AI-driven Practices?

Pickl AI

To confirm seamless integration, you can use tools like Apache Hadoop, Microsoft Power BI, or Snowflake to process structured data and Elasticsearch or AWS for unstructured data. Unify Data Sources Collect data from multiple systems into one cohesive dataset.

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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

ETL Tools: Apache NiFi, Talend, etc. Big Data Processing: Apache Hadoop, Apache Spark, etc. Cloud Platforms: AWS, Azure, Google Cloud, etc. Excel, Tableau, Power BI, SQL Server, MySQL, Google Analytics, etc. Data Warehousing: Amazon Redshift, Google BigQuery, etc.