Rohan Viswanatha Prasad1, Aravind Ayyagari2, Ravi Kiran Pagidi3, Dr S P Singh4, Prof. (Dr) Sandeep Kumar5 & Shalu Jain6
1Visvesvaraya Technological University, India, rohanprasadveb1@gmail.com
2Wichita State University, Dr, Dublin, CA, 94568, USA, aayyagarieb1@gmail.com
3Jawaharlal Nehru Technological University, Hyderabad, India, ravikiran.pagidi@gmail.com
4Ex-Dean, Gurukul Kangri University, Haridwwar, Uttarakhand
5Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation Vadeshawaram, A.P., India er.sandeepsahratia@kluniversity.in
6Maharaja Agrasen Himalayan Garhwal University, Pauri Garhwal, Uttarakhand mrsbhawnagoel@gmail.com
Abstract
The integration of Artificial Intelligence (AI) in data lake implementations has emerged as a transformative approach to enhancing analytics efficiency across various industries. Data lakes, characterized by their ability to store vast amounts of structured and unstructured data, serve as foundational platforms for modern data analytics. However, the sheer volume and diversity of data can hinder timely insights and decision-making processes. This paper explores how AI-driven methodologies can optimize data lake architectures by automating data ingestion, processing, and retrieval, thus facilitating real-time analytics.
AI algorithms can significantly improve data quality and accessibility, ensuring that relevant information is readily available for analysis. Techniques such as machine learning and natural language processing enable the automated classification and tagging of data, leading to enhanced discoverability. Furthermore, AI can assist in predictive analytics, helping organizations identify trends and anomalies swiftly.
By implementing AI-powered solutions, businesses can achieve higher efficiency in their analytics workflows, reduce operational costs, and foster data-driven decision-making. This research highlights best practices for integrating AI with data lake systems, emphasizing the importance of scalable architectures and robust governance frameworks. Ultimately, the synergy between AI and data lakes not only enhances analytics capabilities but also empowers organizations to harness the full potential of their data, driving innovation and competitive advantage in an increasingly data-centric world.
Keywords
AI, data lakes, analytics efficiency, machine learning, natural language processing, data ingestion, data processing, real-time analytics, data quality, predictive analytics, automation, data governance, scalable architecture, data-driven decision-making.
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- Voola, Pramod Kumar, Srikanthudu Avancha, Bipin Gajbhiye, Om Goel, and Ujjawal Jain. 2023. “Automation in Mobile Testing: Techniques and Strategies for Faster, More Accurate Testing in Healthcare Applications.” Shodh Sagar® Universal Research Reports 10(4):420. https://doi.org/10.36676/urr.v10.i4.1356.
- Tangudu, Abhishek, Akshun Chhapola, and Shalu Jain. 2023. “Enhancing Salesforce Development Productivity through Accelerator Packages.” International Journal of Computer Science and Engineering 12(2):73–88. https://drive.google.com/file/d/1i9wxoxoda_pdI1Op0yVa_6uQ2Agmn3Xz/view
- Salunkhe, Vishwasrao, Dheerender Thakur, Kodamasimham Krishna, Om Goel, and Arpit Jain. 2023. “Optimizing Cloud-Based Clinical Platforms: Best Practices for HIPAA and HITRUST Compliance.” Innovative Research Thoughts 9(5):247–247. DOI: https://doi.org/10.36676/irt.v9.i5.1486.
- Salunkhe, Vishwasrao, Shreyas Mahimkar, Sumit Shekhar, Prof. (Dr.) Arpit Jain, and Prof. (Dr.) Punit Goel. 2023. “The Role of IoT in Connected Health: Improving Patient Monitoring and Engagement in Kidney Dialysis.” SHODH SAGAR® Universal Research Reports 10(4):437. DOI: https://doi.org/10.36676/urr.v10.i4.1357.
- Agrawal, Shashwat, Pranav Murthy, Ravi Kumar, Shalu Jain, and Raghav Agarwal. 2023. “Data-Driven Decision Making in Supply Chain Management.” Innovative Research Thoughts 9(5):265–71. DOI: https://doi.org/10.36676/irt.v9.i5.1487.
- Agrawal, Shashwat, Venkata Ramanaiah Chintha, Vishesh Narendra Pamadi, Anshika Aggarwal, and Punit Goel. 2023. “The Role of Predictive Analytics in Inventory Management.” Shodh Sagar Universal Research Reports 10(4):456. DOI: https://doi.org/10.36676/urr.v10.i4.1358.
- Mahadik, Siddhey, Umababu Chinta, Vijay Bhasker Reddy Bhimanapati, Punit Goel, and Arpit Jain. 2023. “Product Roadmap Planning in Dynamic Markets.” Innovative Research Thoughts 9(5):282. DOI: https://doi.org/10.36676/irt.v9.i5.1488.
- Tangudu, A., Chhapola, A., & Jain, S. (2023). Leveraging lightning web components for modern Salesforce UI development. Innovative Research Thoughts: Refereed & Peer Reviewed International Journal, 9(2), 1-10. https://doi.org/10.36676/irt.v9.12.1459
- Pagidi, Ravi Kiran, Santhosh Vijayabaskar, Bipin Gajbhiye, Om Goel, Arpit Jain, and Punit Goel. 2023. “Real Time Data Ingestion and Transformation in Azure Data Platforms.” International Research Journal of Modernization in Engineering, Technology and Science 5(11):1-12. doi:10.56726/IRJMETS46860.
- Mahadik, Siddhey, Fnu Antara, Pronoy Chopra, A Renuka, and Om Goel. 2023. “User-Centric Design in Product Development.” Shodh Sagar® Universal Research Reports 10(4):473. https://doi.org/10.36676/urr.v10.i4.1359.
- . Khair, Md Abul, Srikanthudu Avancha, Bipin Gajbhiye, Punit Goel, and Arpit Jain. 2023. “The Role of Oracle HCM in Transforming HR Operations.” Innovative Research Thoughts 9(5):300. doi:10.36676/irt.v9.i5.1489.
- Mahadik, S., Murthy, P., Kumar, R., Goel, O., & Jain, A. (2023). The influence of market strategy on product success. International Journal of Research in Modern Engineering and Emerging Technology (IJRMEET), 11(7).
- Vadlamani, Satish, Nishit Agarwal, Venkata Ramanaiah Chintha, Er. Aman Shrivastav, Shalu Jain, and Om Goel. 2023. “Cross Platform Data Migration Strategies for Enterprise Data Warehouses.” International Research Journal of Modernization in Engineering, Technology and Science 5(11):1-10. https://doi.org/10.56726/IRJMETS46858.
- Gannamneni, Nanda Kishore, Bipin Gajbhiye, Santhosh Vijayabaskar, Om Goel, Arpit Jain, and Punit Goel. 2023. “Challenges and Solutions in Global Rollout Projects Using Agile Methodology in SAP SD/OTC.” International Journal of Progressive Research in Engineering Management and Science (IJPREMS) 3(12):476-487. doi: https://www.doi.org/10.58257/IJPREMS32323.
- Arulkumaran, Rahul, Dignesh Kumar Khatri, Viharika Bhimanapati, Anshika Aggarwal, and Vikhyat
- Agarwal, Nishit, Rikab Gunj, Shreyas Mahimkar, Sumit Shekhar, Prof. Arpit Jain, and Prof. Punit Goel. 2023. “Signal Processing for Spinal Cord Injury Monitoring with sEMG.” Innovative Research Thoughts 9(5):334. doi: https://doi.org/10.36676/irt.v9.i5.1491.
- Khair, Md Abul, Amit Mangal, Swetha Singiri, Akshun Chhapola, and Om Goel. 2023. “Advanced Security Features in Oracle HCM Cloud.” Shodh Sagar® Universal Research Reports 10(4):493. doi: https://doi.org/10.36676/urr.v10.i4.1360.
- Agarwal, Nishit, Rikab Gunj, Venkata Ramanaiah Chintha, Vishesh Narendra Pamadi, Anshika Aggarwal, and Vikhyat Gupta. 2023. “GANs for Enhancing Wearable Biosensor Data Accuracy.” SHODH SAGAR® Universal Research Reports 10(4):533. https://doi.org/10.36676/urr.v10.i4.1362.
- Anderson, P., & Hu, L. (2023). Exploring Future Directions for AI in Data Lakes: Trends and Innovations. Journal of Data Innovation, 7(2), 120-135.