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1704423 Vol 6 · Issue 11 Download Paper

The Role of Data Science and Analytics in Predictive Modelling and Decision-Making

Dr. Babasaheb Jadhav

Subject area: Science,Engineering and Technology  ·  Area of research: Data Science

Abstract

The phrase "big data" refers to the massive amounts of data that have been created as a direct result of the integration of information systems with the internet, cloud computing, mobile devices, and the Internet of Things (IoT). This has led to the production of "big data." As a consequence of this, there has been a growth in the production of what is known as "big data." A data warehouse, information, and online analytical processing (OLAP) are the three independent components that come together to form this real-time data repository. Together, these three elements constitute the repository as a whole. It is composed of real-time data that can be organised, semi-structured, or unstructured, and all three types are incorporated in its make-up. Both commercial companies and academic institutions have developed novel strategies that are their own in order to get value from massive volumes of data. When it comes to making decisions, leveraging huge datasets as an additional input gives a wide range of options to consider. This research will analyse the role that big data plays in the aforementioned fields in order to facilitate improved decision-making by providing more accurate information. In this piece, we will study how big data may be used to make educated decisions in real time, with the ultimate aim of improving business results as a result of these decisions. The study does a literature review and looks at secondary data in order to provide a conceptual overview of the potential opportunities that big data affords for use in decision making. These were accomplished by looking at secondary data. This article discusses a variety of subjects, including the concept of "big data," its role in the decision-making process, and the competitive advantage that big data offers to a variety of enterprises. In addition to that, the research investigates a technique for the management of data in relation to the process of decision making. It is essential to have a conversation about the issue in order to provide superior options for companies, which will lead to increased levels of competence.

Keywords

Data Science, Data Analytics, Decision-Making

References

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[47] Dr. Shashi Kant Gupta, Hayath T M., Lack of it Infrastructure for ICT Based Education as an Emerging Issue in Online Education, TTAICTE. 2022 July; 1(3): 19-24. Published online 2022 July, doi.org/10.36647/TTAICTE/01.03.A004

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[49] Shaily Malik, Dr. Shashi Kant Gupta, “The Importance of Text Mining for Services Management”, TTIDMKD. 2022 November; 2(4): 28-33. Published online 2022 November doi.org/10.36647/TTIDMKD/02.04.A006

[50] Dr. Shashi Kant Gupta, Shaily Malik, “Application of Predictive Analytics in Agriculture”, TTIDMKD. 2022 November; 2(4): 1-5. Published online 2022 November doi.org/10.36647/TTIDMKD/02.04.A001

How to cite this paper

Dr. Babasaheb Jadhav "The Role of Data Science and Analytics in Predictive Modelling and Decision-Making" Iconic Research And Engineering Journals Volume 6 Issue 11 2023 Page 196-209
Dr. Babasaheb Jadhav "The Role of Data Science and Analytics in Predictive Modelling and Decision-Making" Iconic Research And Engineering Journals, vol. 6, no. 11, May. 2023
Dr. Babasaheb Jadhav (2023). The Role of Data Science and Analytics in Predictive Modelling and Decision-Making. Iconic Research And Engineering Journals, 6(11).
Dr. Babasaheb Jadhav "The Role of Data Science and Analytics in Predictive Modelling and Decision-Making" Iconic Research And Engineering Journals, vol. 6, no. 11, May. 2023.
@article{1704423,
      author = {Dr. Babasaheb Jadhav},
      title = {The Role of Data Science and Analytics in Predictive Modelling and Decision-Making},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {11},
      pages = {196-209},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1704423.pdf},
      abstract = {The phrase "big data" refers to the massive amounts of data that have been created as a direct result of the integration of information systems with the internet, cloud computing, mobile devices, and the Internet of Things (IoT). This has led to the production of "big data." As a consequence of this, there has been a growth in the production of what is known as "big data." A data warehouse, information, and online analytical processing (OLAP) are the three independent components that come together to form this real-time data repository. Together, these three elements constitute the repository as a whole. It is composed of real-time data that can be organised, semi-structured, or unstructured, and all three types are incorporated in its make-up. Both commercial companies and academic institutions have developed novel strategies that are their own in order to get value from massive volumes of data. When it comes to making decisions, leveraging huge datasets as an additional input gives a wide range of options to consider. This research will analyse the role that big data plays in the aforementioned fields in order to facilitate improved decision-making by providing more accurate information. In this piece, we will study how big data may be used to make educated decisions in real time, with the ultimate aim of improving business results as a result of these decisions. The study does a literature review and looks at secondary data in order to provide a conceptual overview of the potential opportunities that big data affords for use in decision making. These were accomplished by looking at secondary data. This article discusses a variety of subjects, including the concept of "big data," its role in the decision-making process, and the competitive advantage that big data offers to a variety of enterprises. In addition to that, the research investigates a technique for the management of data in relation to the process of decision making. It is essential to have a conversation about the issue in order to provide superior options for companies, which will lead to increased levels of competence.},
      keywords = {Data Science, Data Analytics, Decision-Making},
      month = {May},
  }