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What is SDTM-ETL?

A groundbreaking software solution is now available, delivering the best cost-benefit ratio for the creation of SDTM/SEND datasets and define.xml! Known as SDTM-ETL, this software is celebrated as the most economical and valuable tool in the market for generating SDTM and SEND datasets. It only necessitates that your EDC system can export clinical data in the widely accepted CDISC ODM format, which is typically supported by most EDC systems. Remarkably, SDTM-ETL operates independently of SAS®, which means you will not need to bear the expense of a SAS® license or any other statistical software. The software boasts a highly user-friendly graphical interface that enables users to create most mappings effortlessly through straightforward drag-and-drop functionality or mouse clicks. Furthermore, the define.xml files (versions 2.0 or 2.1) are produced automatically, and users can easily input details using intelligent wizards, thereby removing the hassle of tedious XML editing and complicated Excel spreadsheets. Many CROs and service providers have already adopted SDTM-ETL for their regulatory submission processes, making it a favored option in the industry. This innovative tool is not only enhancing clinical data management but is also simplifying the submission journey for numerous organizations. As a result, it stands poised to revolutionize the industry standards and practices in clinical data handling.

What is Apache Hive?

Apache Hive serves as a data warehousing framework that empowers users to access, manipulate, and oversee large datasets spread across distributed systems using a SQL-like language. It facilitates the structuring of pre-existing data stored in various formats. Users have the option to interact with Hive through a command line interface or a JDBC driver. As a project under the auspices of the Apache Software Foundation, Apache Hive is continually supported by a group of dedicated volunteers. Originally integrated into the Apache® Hadoop® ecosystem, it has matured into a fully-fledged top-level project with its own identity. We encourage individuals to delve deeper into the project and contribute their expertise. To perform SQL operations on distributed datasets, conventional SQL queries must be run through the MapReduce Java API. However, Hive streamlines this task by providing a SQL abstraction, allowing users to execute queries in the form of HiveQL, thus eliminating the need for low-level Java API implementations. This results in a much more user-friendly and efficient experience for those accustomed to SQL, leading to greater productivity when dealing with vast amounts of data. Moreover, the adaptability of Hive makes it a valuable tool for a diverse range of data processing tasks.

Media

Media

Integrations Supported

Adobe Real-Time CDP
Amazon EMR
Apache Doris
Apache Hudi
Apache Knox
Apache Spark
BigBI
Causal
ClicData
Cloudera Data Platform
Dataiku
Immuta
MLlib
Mage Static Data Masking
Predibase
Rational BI
SAS Studio
Salesforce Data 360
SecuPi
StreamFlux

Integrations Supported

Adobe Real-Time CDP
Amazon EMR
Apache Doris
Apache Hudi
Apache Knox
Apache Spark
BigBI
Causal
ClicData
Cloudera Data Platform
Dataiku
Immuta
MLlib
Mage Static Data Masking
Predibase
Rational BI
SAS Studio
Salesforce Data 360
SecuPi
StreamFlux

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

XML4Pharma

Company Location

Austria

Company Website

www.xml4pharma.com/SDTM-ETL/

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

hive.apache.org

Categories and Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Categories and Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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