Compare DataBuck vs. Syniti Data Matching

Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.

Enhance your business connectivity, foster growth, and effectively utilize cutting-edge technologies at scale with Syniti’s advanced data matching solutions. Regardless of your data's format or origin, our sophisticated matching software proficiently matches, removes duplicates, integrates, and standardizes data through intelligent, proprietary algorithms. By pushing the limits of traditional data quality approaches, Syniti’s matching solutions empower organizations to become data-centric. Experience an impressive 90% acceleration in data harmonization and a significant 75% decrease in time spent on de-duplication as you transition to SAP S/4HANA. Achieve deduplication, matching, and lookup on billions of records in just 5 minutes, thanks to our performance-ready processing and readily available solutions that function without pre-cleaned data. With the integration of AI, exclusive algorithms, and extensive customization, we enhance matching across intricate datasets while effectively reducing false positives. This innovative approach not only streamlines operations but also positions your business for future growth in a data-driven landscape.