Match Data Pro Description
Match Data Pro is a sophisticated tool for managing data quality that aims to integrate, cleanse, analyze, match, eliminate duplicates, and consolidate records from various files, databases, and systems with remarkable efficiency and accuracy. It features cutting-edge AI-enabled fuzzy matching and adjustable rule-based logic to identify duplicates and inconsistencies within extensive datasets, assisting users in correcting errors, standardizing formats, and generating trustworthy golden records without the need for coding expertise. The tool also offers extensive data profiling with essential metrics to identify quality concerns prior to processing, robust data cleansing functionalities for normalizing and standardizing information, along with address verification features that enhance accuracy. Furthermore, Match Data Pro is equipped with Senzing AI entity resolution and customizable matching algorithms to accommodate minor data variations, ensuring high-performance processing capable of scaling up to millions of records. Additionally, it facilitates project job automation through scheduling, reusable rules, and seamless API integrations, making it a comprehensive solution for effective data management.
Match Data Pro Alternatives
D&B Connect
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.
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DataBuck
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.
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Datactics
Utilize the drag-and-drop rules studio to profile, cleanse, match, and eliminate duplicate data effortlessly. The no-code user interface enables subject matter experts to harness the tool without needing programming skills, empowering them to manage data effectively. By integrating AI and machine learning into your current data management workflows, you can minimize manual tasks and enhance accuracy, while ensuring complete transparency on automated decisions through a human-in-the-loop approach. Our award-winning data quality and matching features cater to various industries, and our self-service solutions can be configured quickly, often within weeks, with the support of specialized Datactics engineers. With Datactics, you can efficiently assess data against regulatory and industry standards, remedy breaches in bulk, and seamlessly integrate with reporting tools, all while providing comprehensive visibility and an audit trail for Chief Risk Officers. Furthermore, enhance your data matching capabilities by incorporating them into Legal Entity Masters to support Client Lifecycle Management, ensuring a robust and compliant data strategy. This comprehensive approach not only streamlines operations but also fosters informed decision-making across your organization.
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Data Ladder
Data Ladder is a company focused on enhancing data quality and cleansing, committed to assisting clients in maximizing their data through services like data matching, profiling, deduplication, and enrichment. Our goal is to maintain simplicity and clarity in our product offerings, ensuring exceptional solutions and customer service at a competitive price for our clients. Our products serve a wide range of users, including those in the Fortune 500, and we take pride in our ability to effectively listen to our clients, which enables us to swiftly enhance our offerings. Our intuitive and robust software empowers business professionals across various sectors to manage their data more efficiently and positively impact their financial performance. Our flagship data quality software, DataMatch Enterprise, has demonstrated its capability to identify approximately 12% to 300% more matches compared to leading competitors such as IBM and SAS in 15 separate studies. With over a decade of research and development to our name, we are continuously refining our data quality solutions. This unwavering commitment to innovation has resulted in more than 4000 successful installations globally, showcasing the trust placed in our products. Ultimately, our mission is to provide superior data management tools that drive success for our clients.
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Pricing
Pricing Starts At:
$27 per month
Free Trial:
Yes
Company Details
Company:
Match Data Pro
Year Founded:
2023
Headquarters:
United States
Website:
matchdatapro.com
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Product Details
Platforms
Web-Based
On-Premises
Types of Training
Training Docs
Training Videos
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Match Data Pro Features and Options
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