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@article{157564,
        author = {Dr. Anita Mahajan and Ajay Varma},
        title = {ANALYSIS OF THE LARGE VOLUMED DATA FILES USING PYTHON PANDAS AND SNOWFLAKE QUERY},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {7},
        pages = {897-901},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=157564},
        abstract = {Due to increasing volume of the data that is being utilized every day, the efforts required to make the data into a proper presentable format is very tedious and time taking task. Since, the latest databases that are currently widely used by the various organizations do provide the integration facilities with the various cloud-based AWS technologies. However, since this kind of operations requires continuous communication with the database server and the AWS server. Also, in case of the data fetching from the staging area through the cloud-based databases, applying the file formatting options and the filtering the rows from the CSV file using various conditions on various columns needs time. That’s why querying the data from the staging files somehow fails in this scenario.},
        keywords = {AWS, cloud-based databases, CSV, Database server.},
        month = {},
        }