Research shows that businesses can lose up to $3 of every $10 of revenue due to poor data quality. With incomplete data known to be
Inaccurate data has real-world implications across industries. In law enforcement, inaccurate data could mean booking the wrong person for a crime. In healthcare, it could
Where there is data, there is regulation. Most of all in the financial industry. Banks, insurance companies and financial institutes must deal with a complex
Address data is semi-structured, making it one of the most challenging components in a data matching activity. For long now, manual data matching methods including
Data errors today can easily cascade into millions in losses and poor data quality can cost businesses up to 31% of their revenue. As the
[vc_row][vc_column][vc_column_text]Accurate product data forms an integral part of a consumer’s purchase decision. From search results to conversions, from brand recognition to comparative product evaluations to
Product matching is the process of matching identical products from various sources through deep learning technologies. In a competitive landscape, where the customer’s spending habit
Unlike traditional stores, digital retailers rely on the effective categorization and dissemination of their product data on their web pages. So having accurately categorized product data on their
As data undergoes a paradigm shift, so do the systems, processes, and approaches involved. Legacy systems are dying. Batch ETL pipelines are slowly becoming obsolete. Ownership is moving away from IT to
Retailer A makes consistently higher sales than Retailer B for the same product, at the same price. Both retailers have 4.5+ star ratings with positive
Data quality (DQ) and data quality management (DQM) is emerging as a needed business strategy in enterprise-level organizations. Although not a new concept (data quality
Picture this: You sell phone cases and offer a wide variety on your online store. A shopper visits your site looking for a specific phone
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Data Ladder offers an end-to-end data quality and matching engine to enhance the reliability and accuracy of enterprise data ecosystem without friction.
