Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.
Type | Title | Date | |
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Category | Data Science Platforms | Dec 17, 2024 | Download |
Product | Reviews, tips, and advice from real users | Dec 17, 2024 | Download |
Comparison | Databricks vs KNIME | Dec 17, 2024 | Download |
Comparison | Databricks vs Amazon SageMaker | Dec 17, 2024 | Download |
Comparison | Databricks vs Microsoft Azure Machine Learning Studio | Dec 17, 2024 | Download |
Title | Rating | Mindshare | Recommending | |
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Microsoft Azure Machine Learning Studio | 3.8 | 5.9% | 93% | 58 interviewsAdd to research |
KNIME | 4.1 | 11.2% | 93% | 58 interviewsAdd to research |
Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.
What are the key features of Databricks?Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.
Databricks was previously known as Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash.
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