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Overview There are a plethora of data science tools out there – which one should you pick up? Here’s a list of over 20. The post 22 Widely Used Data Science and Machine Learning Tools in 2020 appeared first on Analytics Vidhya.
ApacheKafka For data engineers dealing with real-time data, ApacheKafka is a game-changer. Data Visualization and BusinessIntelligenceTableauTableau has revolutionized data visualization, offering a user-friendly platform for creating interactive dashboards and reports.
Key tools include: BusinessIntelligence (BI) Tools : Software like Tableau or Power BI allows users to visualise and analyse complex datasets easily. Machine Learning Algorithms: These algorithms can identify patterns in data and make predictions based on historical trends.
Key tools include: BusinessIntelligence (BI) Tools : Software like Tableau or Power BI allows users to visualise and analyse complex datasets easily. Machine Learning Algorithms: These algorithms can identify patterns in data and make predictions based on historical trends.
Python, SQL, and Apache Spark are essential for data engineering workflows. Real-time data processing with ApacheKafka enables faster decision-making. Understanding Data Engineering Data engineering is collecting, storing, and organising data so businesses can use it effectively.
Best Big Data Tools Popular tools such as Apache Hadoop, Apache Spark, ApacheKafka, and Apache Storm enable businesses to store, process, and analyse data efficiently. TableauTableau is a powerful businessintelligence tool that helps visualize data in an interactive manner through dashboards and reports.
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