Using a self-service tool for data preparation
Data cleansing and data preparation are not the same. When you are cleaning data, you are removing inaccuracies, invalidities, and junk from it. But when
Data cleansing and data preparation are not the same. When you are cleaning data, you are removing inaccuracies, invalidities, and junk from it. But when
Data compliance standards (such as GDPR, HIPAA, and CCPA, etc.) are compelling corporations to revisit and revise their data management strategies. Although each standard enforces
A household consists of multiple separate accounts that belong to individuals who are related and are physically living together.
Duplicate data is a serious problem that affects an organization’s insights, eats up expensive storage space, messes up customer information & leads the business into
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
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
Data Ladder offers an end-to-end data quality and matching engine to enhance the reliability and accuracy of the enterprise data ecosystem without friction.