Papers by Dattatray R Kale
Data quality is highly important for running the effective business process. The real world data ... more Data quality is highly important for running the effective business process. The real world data is spread over the various locations.A collections of these data from the different data sources and presenting the entire collection as a single source is difficult. Data integration involves combining data from numerous dissimilar sources, which are stored using different technologies and present a unified view of the data.Heterogenous and homogenous data is presented at various locations. A big problem in data integration is conflicts occurred into various data sources. Data Inconsistency exists when various and conflicting stories of the same data appear in different places. Data inconsistency shows unreliable information. So in this paper we are presenting the various techniques for finding data inconsistency in data integration.
Industrial Engineering Journal, 2024
Artificial intelligence (AI)-driven predictive analytics is transforming healthcare by facilitati... more Artificial intelligence (AI)-driven predictive analytics is transforming healthcare by facilitating early disease detection, streamlining treatment regimens, and enhancing patient outcomes. This study examines predictive analytics' effects on the healthcare industry, emphasizing its uses, advantages, and approaches. We illustrate how predictive analytics can result in improved health outcomes, more effective healthcare delivery, and cost savings through a review of recent research and case studies. We also go over the difficulties and potential paths ahead for utilizing predictive analytics in clinical practice.
Industrial Engineering Journal ISSN: 0970-2555, 2024
A revolutionary strategy for tackling the problems of environmental sustainability and global foo... more A revolutionary strategy for tackling the problems of environmental sustainability and global food
security is the application of artificial intelligence (AI) in agriculture. AI technologies that optimize
agricultural practices, minimize resource consumption, and minimize environmental impacts include
machine learning, computer vision, and predictive analytics. This study examines the numerous uses
of AI in sustainable agriculture, such as resource management, pest and disease control, crop
monitoring, and precision farming. The conversation focuses on the advantages and difficulties of
implementing AI in agriculture, highlighting how it can improve productivity and sustainability in the
field.
IJSRSET, 2016
Data quality is highly important for running the effective business process. The real world data ... more Data quality is highly important for running the effective business process. The real world data is spread over the various locations.A collections of these data from the different data sources and presenting the entire collection as a single source is difficult. Data integration involves combining data from numerous dissimilar sources, which are stored using different technologies and present a unified view of the data.Heterogenous and homogenous data is presented at various locations. A big problem in data integration is conflicts occurred into various data sources. Data Inconsistency exists when various and conflicting stories of the same data appear in different places. Data inconsistency shows unreliable information. So in this paper we are presenting the various techniques for finding data inconsistency in data integration.
Data quality is highly important for running the effective business process. The real world data ... more Data quality is highly important for running the effective business process. The real world data is spread over the various locations.A collections of these data from the different data sources and presenting the entire collection as a single source is difficult. Data integration involves combining data from numerous dissimilar sources, which are stored using different technologies and present a unified view of the data.Heterogenous and homogenous data is presented at various locations. A big problem in data integration is conflicts occurred into various data sources. Data Inconsistency exists when various and conflicting stories of the same data appear in different places. Data inconsistency shows unreliable information. So in this paper we are presenting the various techniques for finding data inconsistency in data integration.
IEEE International Conference on Blockchain and Distributed Systems Security (ICBDS) Naya Raipur, India. Oct 6-8, 2023, 2023
This paper develops a technique for detecting
violations of conditional functional dependencies ... more This paper develops a technique for detecting
violations of conditional functional dependencies in distributed
database systems. For a given database that has a set of
functional dependencies as a data quality rule, we want to
identify tuples in the database that violate these rules. When
the provided database is a centralized database, there have
been simple SQL-based techniques available for finding
violations of the conditional functional dependencies for this
particular database. However, it is more challenging to detect
violations in distributed databases. Numerous works already
published concentrate on functional dependency error
estimation in centralized settings where data are kept in a
single place, with the aim of reducing the time and space
requirements of the estimation methods. With the design and
execution of the heuristic algorithm, a remedy for breaches of
conditional functional dependencies in the distributed database
is suggested. Our key goal for the distributed data is to solve
the shipment issue. To assess the efficacy of our plan and
algorithm, a series of experiments are created and carried out
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Papers by Dattatray R Kale
security is the application of artificial intelligence (AI) in agriculture. AI technologies that optimize
agricultural practices, minimize resource consumption, and minimize environmental impacts include
machine learning, computer vision, and predictive analytics. This study examines the numerous uses
of AI in sustainable agriculture, such as resource management, pest and disease control, crop
monitoring, and precision farming. The conversation focuses on the advantages and difficulties of
implementing AI in agriculture, highlighting how it can improve productivity and sustainability in the
field.
violations of conditional functional dependencies in distributed
database systems. For a given database that has a set of
functional dependencies as a data quality rule, we want to
identify tuples in the database that violate these rules. When
the provided database is a centralized database, there have
been simple SQL-based techniques available for finding
violations of the conditional functional dependencies for this
particular database. However, it is more challenging to detect
violations in distributed databases. Numerous works already
published concentrate on functional dependency error
estimation in centralized settings where data are kept in a
single place, with the aim of reducing the time and space
requirements of the estimation methods. With the design and
execution of the heuristic algorithm, a remedy for breaches of
conditional functional dependencies in the distributed database
is suggested. Our key goal for the distributed data is to solve
the shipment issue. To assess the efficacy of our plan and
algorithm, a series of experiments are created and carried out