Authors :
Venkata Ramana Reddy Bussu
Volume/Issue :
Volume 9 - 2024, Issue 6 - June
Google Scholar :
https://tinyurl.com/2ap5sbye
Scribd :
https://tinyurl.com/3rb5mk6f
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24JUN417
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The integration of artificial intelligence (AI)
with cloud-based analytics platforms has revolutionized
data processing and decision-making. This research article
explores the synergies between AI, Databricks, and Azure
Data Lake Storage (ADLS), showcasing how organizations
can harness AI capabilities to enhance data analytics
workflows. Through a comprehensive analysis of real-
world use cases, scalability assessments, performance
optimizations, and cost efficiency evaluations, we
demonstrate the transformative impact of AI-driven
analytics on business outcomes.
Keywords :
Azure Databricks, Unity catalog, Databricks Clusters, Spark, Data Intelligence, ML, Data Analysis, commerce, Data/AI, Azure Data Lakes storage.
References :
- Goodfellow, I., et al. "Deep Learning." MIT Press, 2016.
- Databricks: Unified Data Analytics Platform." Databricks, https://databricks.com/.
- Azure Data Lake Storage: Scalable, Secure Data Lake Storage." Microsoft Azure, https://azure.microsoft.com/en-us/services/storage/data-lake-storage/.
- Chollet, F. "Deep Learning with Python." Manning Publications, 2017.
- TensorFlow: An Open Source Machine Learning Framework for Everyone." TensorFlow, https://www.tensorflow.org/.
- PyTorch: An Open Source Deep Learning Platform." PyTorch, https://pytorch.org/.
- Géron, A. "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow." O'Reilly Media, 2019.
- Kumar, A., et al. "Scalable Data Processing with Apache Spark." IEEE Transactions on Parallel and Distributed Systems, vol. 28, no. 4, 2017, pp. 1013-1025.
- Zaharia, M., et al. "Apache Spark: A Unified Analytics Engine for Big Data Processing." Communications of the ACM, vol. 59, no. 11, 2016, pp. 56-65.
- Chiang, K., et al. "Azure Data Lake Storage Gen2: A deep dive into the service." Microsoft Azure Blog, https://techcommunity.microsoft.com/t5/azure-data-lake/azure-data-lake-storage-gen2-a-deep-dive-into-the-service/ba-p/267365.
The integration of artificial intelligence (AI)
with cloud-based analytics platforms has revolutionized
data processing and decision-making. This research article
explores the synergies between AI, Databricks, and Azure
Data Lake Storage (ADLS), showcasing how organizations
can harness AI capabilities to enhance data analytics
workflows. Through a comprehensive analysis of real-
world use cases, scalability assessments, performance
optimizations, and cost efficiency evaluations, we
demonstrate the transformative impact of AI-driven
analytics on business outcomes.
Keywords :
Azure Databricks, Unity catalog, Databricks Clusters, Spark, Data Intelligence, ML, Data Analysis, commerce, Data/AI, Azure Data Lakes storage.