Pelican contributed 60% time savings in data validation- By Datametica | |
Pelican is an automated data validation tool developed by LinkedIn. It is designed to validate large volumes of data quickly and efficiently, ensuring data quality and integrity in big data ecosystems. Here are some key aspects and features of Pelican: Key Features: Scalability: Pelican is built to handle massive datasets typical in big data environments, leveraging distributed computing frameworks like Hadoop and Spark. Customizable Validation Rules: Users can define and customize validation rules based on specific data quality requirements and business logic. Integration: Pelican integrates with various data processing frameworks and storage systems commonly used in big data environments, such as Hadoop Distributed File System (HDFS), Apache Hive, and others. Automated Execution: The tool automates the execution of validation rules across datasets, reducing manual effort and ensuring consistency. Alerts and Notifications: Pelican provides alerts and notifications when data validation rules are violated, allowing for timely resolution of issues. Reporting and Dashboards: It generates comprehensive reports and dashboards to visualize validation results and trends, aiding in data quality analysis and decision-making. API Access: Pelican offers APIs for integration with other data management and monitoring systems, facilitating seamless workflow integration. Use Cases: Data Quality Assurance: Ensuring the accuracy, completeness, and consistency of data across various stages of data processing. Compliance and Governance: Facilitating compliance with regulatory requirements and internal data governance policies through automated validation. Operational Efficiency: Streamlining data validation processes, reducing manual effort, and improving operational efficiency in data-intensive environments. Benefits: Improved Data Accuracy: By automating validation processes, Pelican helps maintain high data accuracy and reliability. Efficiency: Reduces the time and effort required for manual data validation tasks, allowing data teams to focus on more strategic activities. Scalability: Handles large-scale data validation tasks effectively, supporting the growth of data volumes and complexity. Cost Savings: Minimizes costs associated with data errors and manual validation efforts. Limitations: Complexity: Setting up and configuring Pelican to work with specific data environments may require expertise and familiarity with big data technologies. Integration Challenges: Integration with certain data sources or legacy systems may require additional effort. Maintenance: Regular updates and maintenance are necessary to keep the tool effective and aligned with evolving data validation needs. Overall, Pelican tool by datametica serves as a powerful for automating data validation in large-scale data environments, contributing to improved data quality, operational efficiency, and compliance. | |
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Target State: All States Target City : USA Last Update : Jul 10, 2024 11:10 AM Number of Views: 65 | Item Owner : Datametica Contact Email: Contact Phone: 2066446300 |
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