All Resources
Matching Evolution: Finding Matches Across the Enterprise and Fine Tuning Results the Modern Way
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
Manage Your Retail Business with a Robust Product Data Quality Solution
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
Why Your Organization Must Have a Data Quality Management Plan to Be Ahead of the Game
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
Product Taxonomy 101: Categorizing Your Store Hierarchy to Increase Sales
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
Data Enrichment Benefits – Increase Sales Efficiency & Customer Satisfaction by 50%
Data, an organization’s intellectual asset, must be treated and regularly enriched to remain useful and valuable. Over 80% of companies we’ve worked with, — including
Data Enrichment Guide – How to Enrich and Optimize CRM Data for Accurate Insights
44% of companies lose over 10% of annual revenue due to poor-quality CRM data. This shows how many CRM users’ trust in their data is
A Quick Guide to Data Merge Purge
Having delivered merge purge solutions to clients for over a decade, we consider merge purge operations to be an essential function in business operations like
Self-service Data Preparation Tools – Reduce Your Reliance on IT & Complex ETL Processes
Data preparation tools have been around for quite some time now. Most of these tools though require users to be proficient in programming languages &
A Quick Guide to Data Preparation Software, Solutions & Best Practices
As companies are spending billions of dollars investing in big data with the hopes of turning data into money, the need for efficient, easy-to-use data preparation
