Real-time Analytics in Cloud-based Data Solutions

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[35] Sumit Shekhar, SHALU JAIN, DR. POORNIMA TYAGI, "Advanced Strategies for Cloud Security and Compliance: A Comparative Study," IJRAR - International Journal of Research and Analytical Reviews (IJRAR), E-ISSN 2348-1269, P- ISSN 2349-5138, Volume.7, Issue 1, Page No pp.396-407, January 2020, Available at: [IJRAR](http://www.ijrar IJRAR19S1816.pdf)

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@article{1702986,
      author = {Vamsee Krishna Ravi, Abhishek Tangudu, Ravi Kumar, Dr. Priya Pandey, Aravind Ayyagari; Prof. (Dr) Punit Goel},
      title = {Real-time Analytics in Cloud-based Data Solutions},
      journal = {Iconic Research And Engineering Journals},
      year = {2021},
      volume = {5},
      number = {5},
      pages = {288-305},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1702986.pdf},
      abstract = {Real-time analytics has emerged as a pivotal component in cloud-based data solutions, enabling organizations to derive actionable insights from vast streams of data instantaneously. As businesses increasingly migrate their operations to cloud environments, the demand for real-time data processing has surged. This paper explores the significance of real-time analytics in enhancing decision-making processes, operational efficiency, and customer engagement. By leveraging cloud infrastructure, organizations can harness advanced analytics tools and technologies, such as machine learning and data streaming, to analyze data as it is generated.
The integration of real-time analytics into cloud-based solutions offers numerous benefits, including improved responsiveness to market changes, enhanced predictive capabilities, and the ability to monitor systems continuously. Furthermore, it facilitates the automation of business processes, allowing for proactive issue resolution and strategic planning. This research also addresses the challenges associated with implementing real-time analytics, such as data latency, scalability, and security concerns.
By evaluating various case studies and industry applications, this study demonstrates how organizations can effectively implement real-time analytics within their cloud frameworks to optimize performance and drive innovation. Ultimately, this paper underscores the transformative potential of real-time analytics in cloud-based data solutions, advocating for its adoption as a strategic imperative for businesses aiming to remain competitive in an increasingly data-driven landscape.},
      keywords = {Real-time analytics, cloud-based data solutions, data streaming, machine learning, operational efficiency, decision-making, predictive analytics, business automation, data latency, scalability, security concerns, industry applications, competitive advantage.},
      month = {November},
  }