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Integrating Clinical Research Data from Multiple Vendors and Sources into an Enterprise Data Warehouse Enabled Improved Clinical Research Analysis
[/vc_column_text][vc_column_text css=”.vc_custom_1765261339378{margin-top: 0px !important;margin-bottom: 35px !important;}” el_class=”text-block”]Established in 1997, the client is a world leader in developing and commercializing first-or-best-in-class therapies for rare genetic diseases. Headquartered in California, US, the client has operations spread across 20+ countries and has 2500+ employees worldwide.[/vc_column_text][vc_column_text css=”.vc_custom_1765261637785{margin-top: 0px !important;margin-bottom: 35px !important;}” el_class=”text-block”]
Background
[/vc_column_text][vc_column_text css=”.vc_custom_1765261445628{margin-top: 0px !important;margin-bottom: 35px !important;}” el_class=”text-block”]The customer was collecting clinical research data from multiple sources and in various formats, which was making it difficult to integrate and analyze the data. This was leading to data inconsistencies and errors, which was compromising the accuracy and completeness of the study results. Hence, the customer conducted a due diligence exercise to determine the best mechanism to analyze the clinical research data received from multiple sources.[/vc_column_text][vc_column_text css=”.vc_custom_1765262431513{margin-top: 0px !important;margin-bottom: 35px !important;}” el_class=”text-block”]
DiLytics’ Solution
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DiLytics implemented a solution on Oracle Analytics that involved:
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- Extended EDW to create new tables and add columns to existing tables
- Developed shell script to move data files from SFTP server location to Data Integration server so that extract, transform, and load process (ETL) can pick up the data from flat files for loading into EDW
- Developed Data Integration layer using Informatica to extract clinical research data from flat files provided by the customer vendors into staging tables
- Developed data validation logic to validate the data in the flat files provided by the customer vendors
- Developed ETL code using Informatica to load clinical research data from the EDW staging tables into the designed data model
- Collaborated with the customer in integrating data from EDW into Board
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Business Benefits
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Key business benefits to the client included:
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- Improved decision-making
- Improved accuracy and completeness of clinical research data
- Increased efficiency in the clinical research process
- Superior competitive advantage due to improved collaboration among customer and clinical research data vendors
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DiLytics Delivers
[/vc_column_text][/vc_column][vc_column width=”1/3″][vc_custom_heading text=”View all Success Stories →” font_container=”tag:h6|font_size:16px|text_align:right|color:%23dd3333|line_height:26px” use_theme_fonts=”yes” css=”.vc_custom_1660717315754{margin-top: 0px !important;margin-bottom: 10px !important;}” el_class=”font-weight-medium” link=”url:https%3A%2F%2Fdilytics.com%2Fsuccess-stories%2F|title:Success%20Stories”][/vc_column][vc_column css=”.vc_custom_1661424713241{margin-bottom: 25px !important;}”][rt_case_study_style case_study_style_variation=”seven” case_study_display_filter=”no” case_study_enable_title=”yes” case_study_enable_excerpt=”yes” case_study_spacing=”30″ case_study_looping_sort=”ASC” no_of_case_studies=”3″][/vc_column][/vc_row]