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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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A Comprehensive Guide to the main components of Big Data

Pickl AI

Cloud Storage: Services like Amazon S3, Google Cloud Storage, and Microsoft Azure Blob Storage provide scalable storage solutions that can accommodate massive datasets with ease. Key tools include: Business Intelligence (BI) Tools : Software like Tableau or Power BI allows users to visualise and analyse complex datasets easily.

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A Comprehensive Guide to the Main Components of Big Data

Pickl AI

Cloud Storage: Services like Amazon S3, Google Cloud Storage, and Microsoft Azure Blob Storage provide scalable storage solutions that can accommodate massive datasets with ease. Key tools include: Business Intelligence (BI) Tools : Software like Tableau or Power BI allows users to visualise and analyse complex datasets easily.

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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.