Role of bigdata in clinical data management

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In the past, clinical trials have used only structured, clinically-sourced data, which was relatively easy to organize and mine. But, today to analyze large amount of data quickly, things have changed. By 2020 the total amount of data stored is supposed to be 50 times larger than today.

Obstacles in clinical data management Data Completeness Quality Cleaning Inconsistent Data Data Governance

Implications of Bigdata in Developing Health Care

How does big data work for clinical trials?

Today, the cloud allows us to include terabytes of unstructured data from many different, real-world data sources. With the ability to scale technology to collect this unstructured, real-world data from myriad systems, organize it into comparable formats, analyze it, and visualize the results.

How can unstructured data be organized and included?

The key may be a federated approach to store data from various domains in multiple repositories. In addition to having the ability to trace trial data from beginning to end and speed the review/query resolution, they will also offer ease of access to data management and integrated downstream analysis across all data types. Finally, we will offer advanced analytics and patient data visualizations for better, faster, actionable insights.

Bigdata transformation can't happen until everyone in your organization can find, trust, secure, and use critical data. To bring users, processes, and policies together enterprise-wide, you need a holistic, end-to-end data governance solution.

• Inducing a data proactive and data driven culture
• Increasing collaboration and integration within the company
• Using predictive analytics and Artificial Intelligence to receive optima real-time/near-time recommendations
• Employing strong data governance measures with effective processes to protect data

How it works and key technologies

Here, several types of technology work together to help you get the most value from your information. Here are the biggest players: Machine Learning, Data Mining, Data Mining, Predictive Analytics, Text Mining (uses ML or NLP- Natural Language Processing).

As a trusted Clinical Data Management services provider, we want to make sure you know how AI & Bigdata work for “Clinical Data Management”.

References: https://www.jmir.org/2005/1/e5/?xml

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Conférence Annuelle 2018 Data Management Biomédical

Tuesday, November 19 2019 from 9am to 6pm - Cité Universitaire Internationale de Paris

Topics that will be covered: Using clinical data - Archiving data - Inspection readiness - CSV and Data Integrity - EHR & Blockchain

Deadline for registering: November 11 Click here for more details

Society for Clinical Data Management - Webinar

Understanding the Regulatory Direction and How To Meet It – The Path through RBM to Quality by Design on November 12, 2019 Click here to learn more about the webinar and register