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Data Analytics > What is required for big data analytics?
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What is required for big data analytics?

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Data Analyst with 10 years of experience in Fintech, Product ,and IT Services

### Requirements for Big Data Analytics: 1. **Data Sources:** Large volumes of data from various sources like social media, sensors, and databases.2. **Data Storage:** Scalable storage solutions such as Hadoop Distributed File System (HDFS) or cloud storage like AWS S3.3. **Data Processing Tools:**...
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### Requirements for Big Data Analytics: 1. **Data Sources:** Large volumes of data from various sources like social media, sensors, and databases.2. **Data Storage:** Scalable storage solutions such as Hadoop Distributed File System (HDFS) or cloud storage like AWS S3.3. **Data Processing Tools:** Technologies like Apache Spark and Hadoop to process and manage large datasets.4. **Data Analysis Tools:** Software for statistical analysis and machine learning, such as R, Python, and SQL.5. **Data Visualization Tools:** Platforms like Tableau, Power BI, or custom dashboards to visualize insights.6. **Infrastructure:** High-performance computing resources and scalable cloud services. ### Summary:Big data analytics requires robust storage, processing, and analysis tools to handle and make sense of large volumes of data. read less
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I am online Quran teacher 7 years

### Requirements for Big Data Analytics: 1. **Data Sources:** Large volumes of data from various sources like social media, sensors, and databases.2. **Data Storage:** Scalable storage solutions such as Hadoop Distributed File System (HDFS) or cloud storage like AWS S3.3. **Data Processing Tools:** Technologies...
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### Requirements for Big Data Analytics: 1. **Data Sources:** Large volumes of data from various sources like social media, sensors, and databases.2. **Data Storage:** Scalable storage solutions such as Hadoop Distributed File System (HDFS) or cloud storage like AWS S3.3. **Data Processing Tools:** Technologies like Apache Spark and Hadoop to process and manage large datasets.4. **Data Analysis Tools:** Software for statistical analysis and machine learning, such as R, Python, and SQL.5. **Data Visualization Tools:** Platforms like Tableau, Power BI, or custom dashboards to visualize insights.6. **Infrastructure:** High-performance computing resources and scalable cloud services. ### Summary:Big data analytics requires robust storage, processing, and analysis tools to handle and make sense of large volumes of data. read less
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