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.
Learn more
Your first-party data can be used to unlock its full potential. D&B Connect is a self-service, customizable master data management solution that can scale. D&B Connect's family of products can help you eliminate data silos and bring all your data together. Our database contains hundreds of millions records that can be used to enrich, cleanse, and benchmark your data. This creates a single, interconnected source of truth that empowers teams to make better business decisions. With data you can trust, you can drive growth and lower risk. Your sales and marketing teams will be able to align territories with a complete view of account relationships if they have a solid data foundation. Reduce internal conflict and confusion caused by incomplete or poor data. Segmentation and targeting should be strengthened. Personalization and quality of marketing-sourced leads can be improved. Increase accuracy in reporting and ROI analysis.
Learn more
Match2Lists
Match2Lists provides the quickest, simplest, and most precise solution for matching, merging, and de-duplicating your data. With our Match2D&B feature, you can seamlessly enhance your datasets with Dun & Bradstreet information whenever needed. Within a matter of minutes, you can rid your data of duplicates and integrate disparate raw data into impactful insights. Our primary goal is to achieve the highest match results possible for our clients. Before we developed Match2Lists, we operated analytics and data visualization firms, utilizing various "fuzzy" matching software available in the industry. Frustrated by their inadequate match outcomes, we dedicated ten years to crafting the most sophisticated data matching algorithms. Our secondary goal is to optimize time: we aim to allow our clients to devote less time to data matching and cleansing, and instead focus on analysis and execution. This led us to implement our cutting-edge matching logic on the fastest in-memory cloud computing infrastructure we could find, which can process 200 million records in just 30 seconds. Now, businesses can enjoy enhanced productivity and make informed decisions rapidly.
Learn more
DataMatch
The DataMatch Enterprise™ solution is an intuitive data cleansing tool tailored to address issues related to the quality of customer and contact information. It utilizes a combination of unique and standard algorithms to detect variations that are phonetic, fuzzy, miskeyed, abbreviated, and specific to certain domains. Users can establish scalable configurations for various processes including deduplication, record linkage, data suppression, enhancement, extraction, and the standardization of both business and customer data. This functionality helps organizations create a unified Single Source of Truth, thereby enhancing the overall effectiveness of their data throughout the enterprise while ensuring that the integrity of the data is maintained. Ultimately, this solution empowers businesses to make more informed decisions based on accurate and reliable data.
Learn more
