Add-on promises better data quality in distributed environments
Data quality specialist Syncsort today launched an addition to its Trillium family of data quality solutions that specifically targets large volumes of enterprise data on-premises or in the cloud.
The Lowdown: The new Trillium DQ for Big Data offers profiling, cleansing, standardization, and matching, including strong entity resolution on distributed architectures, on-premises, and in the cloud. The capabilities are aimed at helping organizations with Big Data programs improve the quality of data used in insights and governance initiatives such as fraud detection, anti-money laundering, omni-channel marketing, predictive analytics, data science, and machine learning.
The Details: For both cloud and on-premises applications, Trillium DQ for Big Data features:
• A unified solution to address quality issues in the data lake
• Scalable profiling of high volumes of data and comprehensive matching of complex entities to help ensure data quality and build a 360-degree view of key entities for business-critical applications and AI pipelines within the data lake
• An interface for non-technical users with built-in business rules and drill-down capabilities used to discover DQ issues and anomalies
• Design-once-deploy-anywhere design for running data quality jobs natively to Big Data execution frameworks such as Hadoop MapReduce and Spark or through real-time services with no additional coding or tuning requirements
The Buzz: “Recent Syncsort research revealed more than 72 percent of respondents reported sub-optimal data quality negatively impacting business decisions,” said Dr. Tendu Yogurtcu, CTO at Syncsort. “Almost half also found un-trustworthy results or inaccurate insights from analytics were due to a lack of quality in the data fed into downstream applications such as AI and machine learning. By providing integrated data profiling, cleansing, standardization, and matching on distributed and cloud platforms, we are empowering organizations to resolve the data quality issues and drive significant business value from their data.
“Analysis of data quality process flow results is essential for data analysts to support continuous data quality improvement and deliver optimal results within targeted time windows,” Yogurtcu added. “With the new Syncsort Trillium product, we are enabling them to easily profile large, more diverse data sources in a few simple steps, explore the results of the profiling from a business-friendly user interface to discover new insights and issues, and monitor the quality of their data to allow delivery of reports and findings readily to business leaders. Data analysts and data quality specialists can also design, develop, and deploy highly scalable data quality solutions in their data pipelines or in real time to cleanse, standardize, match, and resolve entities without technical expertise in Big Data and distributed architectures.”