Use the comparison tool below to compare the top Data Matching software on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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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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WinPure Clean & Match
WinPure
$999 2 RatingsClean & Match, WinPure's award winning data cleansing and data matching software suite is designed to improve the accuracy of consumer or business data. This software suite can be used to clean, correct, and deduplicate mailing lists, spreadsheets, CRMs, and databases. WinPure™, Clean & Match will save your business money and time. * Increase accuracy of any list, spreadsheet, database, CRM, etc. * Windows software is locally installed so you don't have to worry about security. All processing takes place on your own systems. * Use built-in phonetic and fuzzy match algorithms to save hours cleaning duplicate records from your databases or lists. * Low-cost licences with World Class Support & Training. * Free Demo with Live Online Training Available -
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Narrative
Narrative
$0With your own data shop, create new revenue streams from the data you already have. Narrative focuses on the fundamental principles that make buying or selling data simpler, safer, and more strategic. You must ensure that the data you have access to meets your standards. It is important to know who and how the data was collected. Access new supply and demand easily for a more agile, accessible data strategy. You can control your entire data strategy with full end-to-end access to all inputs and outputs. Our platform automates the most labor-intensive and time-consuming aspects of data acquisition so that you can access new data sources in days instead of months. You'll only ever have to pay for what you need with filters, budget controls and automatic deduplication. -
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Senzing
Senzing
Senzing® entity resolution API software provides the most advanced, affordable, and easy-to-use data matching and relationship detection capabilities available. With Senzing software, you can automatically resolve records about people, organizations and their relationships in real time as new data is received. The highly accurate and complete views Senzing software delivers allow you to reduce costs and enable new revenue opportunities. Senzing provides a set of libraries that that can be deployed on premises or in the cloud, in a variety of ways, depending on your architecture and environment requirements. Data remains in your ecosystem and never flows to Senzing, Inc. Minimal data preparation is required when and no tuning, training or entity resolution experts are needed. A free proof of concept can be completed in about six hours on AWS or bare metal. You can try the Senzing API on up to 100K records for free. -
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Match2Lists
Match2Lists
$95 per monthMatch2Lists is the fastest and easiest way to match, merge and de-duplicate data. You can enrich your data with Dun & Bradstreet information using our Match2D&B option. You can quickly clean up duplicates and combine data from multiple sources into powerful information in a matter of minutes. Our first goal is to provide maximum match results for customers. Before Match2Lists was created, we were data visualisation and analytics companies. We also used the most "fuzzy" matching technology on the market. We spent 10 years creating the most advanced data matching logic to overcome their low match results. Our second goal is to save time. We want our customers not to spend as much time cleansing and matching data, but more time analysing and executing. Our advanced matching logic was implemented on the fastest in-memory cloud computing architecture that we could find. It is capable of matching 200,000,000 records in 30 seconds. -
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OpenRefine
OpenRefine
OpenRefine (previously Google Refine), is a powerful tool to work with messy data. It can clean it, transform it into another format, and extend it with web services or external data. OpenRefine keeps your data secure on your computer until you share it or collaborate with others. Unless you wish it to, your private data will never leave your computer. It works by installing a small server on your computer. You then use your web browser for interaction with it. OpenRefine allows you to explore large data sets easily. Watch the video below to learn more about this functionality. OpenRefine can link and extend your data with many webservices. OpenRefine can also upload your cleaned data to Wikidata. -
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WinPure MDM
WinPure
WinPure™, MDM, is a master data management system that aligns with your company to provide a single view of all your data. It also includes functions and features to help manage your data. These features are available as a free download from the clean & matching enterprise edition. They have been repurposed for easy web-based data prep and MDM operations. There are many ways to clean, standardize, and transform data in dozens different formats. Industry-leading data matching and error-tolerant technologies. It is simple and easy to configure survivorship technology. The general benefits include a lower cost and a faster time to market. It is easy to use, requires minimal training, and can be implemented quickly. Faster MDM and systems deployments will result in better business results. Simple and easy data preparation tools, batch loads that are faster and more accurate. Flexible and efficient interconnectivity via API with other databases and systems. Accelerate the time it takes to create synergies in M&A. -
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LinkageWiz
LinkageWiz
$199 one-time paymentThe powerful Probabilistic Data Matching algorithms use common identifiers like name, date, sex and address. Data can be imported from many different desktop and corporate databases systems. Data matching software can detect potential matches up to 99%. This software can help businesses generate additional revenue or reduce costs. It can also detect fraud more effectively. And, for medical research, it can make the difference between a successful and unsuccessful research project. LinkageWiz is quick, easy to use, and offers outstanding value because it combines many of the features offered by other products into one package. -
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Data Cleansing & Matching
Data Cleansing & Matching
$99.95 one-time paymentThis Matching software includes a matching engine that can transform and standardize your data, remove and compare two projects, and match records from marketing lists or databases. Our data matching software uses the most current technologies. Use our data matching software or test our data scrubbing tool today. Update the main database, insert a new record, and then get statistics. Only insert a new record and update your main database. Get statistics by inserting a new record to the main database. Update the main database with matching information to get statistics. Remove matches from the main database to get statistics. -
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datuum.ai
Datuum
Datuum is an AI-powered data integration tool that offers a unique solution for organizations looking to streamline their data integration process. With our pre-trained AI engine, Datuum simplifies customer data onboarding by allowing for automated integration from various sources without coding. This reduces data preparation time and helps establish resilient connectors, ultimately freeing up time for organizations to focus on generating insights and improving the customer experience. At Datuum, we have over 40 years of experience in data management and operations, and we've incorporated our expertise into the core of our product. Our platform is designed to address the critical challenges faced by data engineers and managers while being accessible and user-friendly for non-technical specialists. By reducing up to 80% of the time typically spent on data-related tasks, Datuum can help organizations optimize their data management processes and achieve more efficient outcomes. -
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DataMatch
Data Ladder
DataMatch Enterprise™, a highly visual data cleansing tool, is specifically designed to address customer and contact data quality problems. The platform uses a variety of proprietary and standard algorithms to identify phonetic and domain-specific variations. You can create scalable configurations that allow for deduplication, record linkage, suppression enhancement, extraction, standardization, standardization, and standardization of customer and business data. This will maximize the impact of your data throughout the enterprise. -
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TIBCO EBX
TIBCO
One solution to manage, govern, and consume all shared data assets. TIBCO EBX™, software helps organizations avoid silos by providing an all-in-one solution to managing data assets throughout the enterprise. You will thrive when you can share and manage all your data assets. Data is vital for mission-critical operations, analytical process, and customer experience. Business teams cannot rely on outdated tools or office automation to manage the constantly changing data. EBX™, a leader in Master Data Management (MDM), and a pioneer in data asset administration, offers a single, innovative solution for managing, governing, consuming and distributing all shared data assets. -
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Egon
Ware Place
Geocoding and address quality software. Validate, deduplicate, and maintain accurate and deliverable address information. Data quality is the ability to verify the accuracy and completeness of certain data. Data quality and postal address verification involves integrating data into any address database to ensure it is reliable and serves its intended purpose. There are many sectors and operations that rely on postal addresses, such as shipping and data entry, such as geomarketing and statistics, such as transportation. Operations tuning is key to ensuring significant logistics and economic savings for enterprises. This add-value is important to make work easier, more efficient. Egon is an online data quality system that can be accessed via the internet. -
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Data Ladder
Data Ladder
Data Ladder is a data cleansing and quality company that helps you "get the best out of your data." We offer data matching, profiling and deduplication as well as enrichment. Our product offerings are simple and easy to understand. This allows us to provide excellent customer service and a great solution for our customers. Our products are used by Fortune 500 companies. We are proud of our reputation for listening to our customers, and constantly improving our products. Our powerful, user-friendly software allows business users from all industries to manage their data more efficiently and improve their bottom line. DataMatch Enterprise, our data quality software suite, found approximately 12%-300% more matches than the leading software companies IBM or SAS in 15 different studies. We have over 10 years of experience in R&D and counting. We are constantly improving our data-quality software solutions. This dedication has resulted in more than 4000 installations around the world. -
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exorbyte
exorbyte
Intelligent technologies are required to make the most of all data. This is due to growing data volumes, digital transformations and increased compliance requirements. Exorbyte provides customized Search & Match solutions that make all data accessible to humans and machines at lightning speed. No matter the quality, structure, format, or language of the data. The master data search allows for comprehensive, fuzzy searches in real-time and millions of records using just one search field. Fully adjustable, error-tolerant, flexible across all fields. Master data comparison allows you to compare whole or part of data records with the master database. There are no restrictions and no errors across databases. The master data recognition extracts identity from documents, letters, or faxes and then compares them to reference data. Fuzzy data matching and intelligent extract data. -
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Datactics
Datactics
Drag-and-drop rules studio allows you to profile, clean, match, and deduplicate data. Lo-code UI is a user interface that requires no programming skills. This puts power in the hands subject matter experts. You can add AI and machine learning to your existing data management process to reduce manual effort, increase accuracy, and provide full transparency on machine-led decisions. Our self-service solutions offer award-winning data quality, matching capabilities across multiple industries and are quickly configured with specialist assistance from Datactics data engineers. Datactics makes it easy to measure data against industry and regulatory standards, fix breaches in bulk, and push into reporting tools. Chief Risk Officers have full visibility and audit trails. Datactics can be used to augment data matching with Legal Entity Masters to manage client lifecycle management. -
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Syniti Data Matching
Syniti
Syniti's data match solutions will help you build a more connected company, drive growth, or leverage new technologies at scale. No matter what data source or shape, our matching software matches, unifies, unifies and harmonizes data using proprietary algorithms. Syniti's matching software is innovative in data quality and empowers data-driven businesses. You will be able to accelerate data harmonization by 90%, and save 75% on de-duplication during your journey to SAP S/4HANA. With performance-ready processing and ready-to-go solutions that don’t require clean data, you can perform deduplication, matching, or lookup on billions upon billions of records in just 5 minutes. AI, proprietary algorithms, steep customization, and high-quality matches maximize matches across complex datasets, and minimize false positives. -
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Kalinda
Kalinda
Legislative restrictions on what information can be shared and under which circumstances. Data matching and discovery are used to speed up information sharing between agencies in relation to specific cases. Kalinda's core is a machine-learning-based algorithm that matches person records between multiple agencies using personal characteristics (such name, birth date, etc.) and the characteristics related people. Sometimes, in-depth investigations require the ability to examine relationships between people and with locations even if only partial information is available. Kalinda can answer partial-match questions about person, location, and relationship information. Kalinda uses extended algorithms to find records that are similar to the matches based on probabilistic records matching. -
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Firstlogic
Firstlogic
Validate and verify your address information by comparing them with official Postal Authority databases. You can increase delivery rates, reduce returned mail, and receive postal discounts. Connect address datasources with our enterprise-class cleansing transforms. Once you have connected your address datasources, you will be able to validate and verify it. You can increase delivery rates, reduce returned mail, and get postal discounts. Identify the data elements in your address data and separate them into their parts. Correct common spelling errors and format your address data to conform with industry standards. This will improve mail delivery. Verify that an address exists against the USPS address database. You can verify whether the address is residential, business, or if it is deliveryable by USPS Delivery Point Validation. Merge validated data from multiple sources to create customized output files for your organization's workflow. -
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Experian Data Quality
Experian
Experian Data Quality is a leader in data quality and data management solutions. Our comprehensive solutions can validate, standardize and enrich customer data. We also profile and monitor it to ensure that it is suitable for purpose. Our software can be customized to any environment and any vision with flexible SaaS or on-premise deployment models. Real-time address verification solutions allow you to keep your address data current and preserve the integrity of your contact information. Comprehensive data quality management solutions allow you to analyze, transform, and manage your data. You can even create data processing rules specific to your business. Experian Data Quality's phone validation tools can help you improve your mobile/SMS marketing efforts. -
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matchit
360Science
Matchit®, the core of our matching software, is specifically designed to produce results that are human-like. It does this at scale and without any preprocessing. Matchit uses Artificial Intelligence, which is a proprietary phonetic algorithm and lexicons as well as a contextual scoring engine to overcome the inconsistencies and challenges often found in business and contact data. Matching logic is a combination function and off-the shelf fuzzy algorithms that produces an alphanumeric value. Conventional matching solutions require the user to define it. This alphanumeric value (or'match key') is used to compare two records and ultimately find matches. Matchit is not like traditional matching solutions. It doesn't rely solely on one comparison between match keys to find matches. Matchit evaluates records contextually by running a variety comparisons and scoring them individually to determine the similarity between all elements in your data. -
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QDeFuZZiner
QDeFuZZiner
QDeFuZZiner software considers project as a basic entity. Each project has definitions for two source datasets that can be imported and analyzed (the "left dataset" or "right dataset"), along with variable numbers of corresponding solutions. These are stored definitions of how fuzzy match analysis can be performed. Each project is given a unique project tag upon creation. Raw data importing to the server is done by assigning a unique project tag to each project. Imported tables are always tagged with the project name to ensure their uniqueness. QDeFuZZiner creates various indexes on the PostgreSQL database during import and later, during solution creation and execution. This facilitates fuzzy data matching. Datasets can be imported from source spreadsheets (.xlsx or.ods), or CSV (comma separated value) flat files to the server database. The left and right databases tables are then created, indexed, and processed. -
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Golden Record
Golden Record
Many data is stored by businesses in different systems and applications across departments. These include CRMs, marketing automation platforms and POS systems. Golden Record is data matching software that links business data across all systems. It can match and dedupe records and keeps them synchronized in real-time. You can export data from all your systems to spreadsheets or CSV files. Then, you can spend a lot of time manually comparing fields, creating new corrected CSVs, then import them back into your systems. A data expert can help you analyze your data and create a custom application that links it all. You can spend months configuring data movement software to connect existing systems.
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Overview of Data Matching Software
Data matching software is a type of program that helps organizations compare two or more sets of data in order to find discrepancies and inconsistencies. This type of software can be used for many different tasks, such as verifying customer data, identifying duplicate records, managing auditing processes, tracking customer orders, and more.
The key component of most data-matching software is a database. This database contains information about the records that need to be compared. When the program runs, it searches through this database looking for any matches between the two sets of data. If it finds any matches, it then flags these discrepancies and gives the user an alert so they can take action accordingly.
Another key feature of modern data-matching software is its ability to identify and manage duplicate records. This can be especially useful for businesses dealing with large amounts of customer data that needs to remain organized and up-to-date. By using this software, businesses can ensure that their customers’ information remains in one place without any risk of overlap or confusion between different records.
One important aspect of using this type of software is its accuracy in finding matches between different sets of data. Thanks to advanced algorithms developed by engineers over the years, these programs are now able to quickly scan through huge databases and accurately detect any differences or inconsistencies between them. Additionally, most modern versions come with powerful tools such as visualization solutions which allow users to easily interpret their results at a glance.
Finally, many companies also use data matching software specifically tailored towards security purposes–such as fraud detection or identity verification services–in order to protect their systems from potential malicious attacks or unauthorized access attempts by criminals. These specialized programs are designed with highly sophisticated features which enable them to accurately identify suspicious activity across networks in real time and take action accordingly if needed.
Overall, data matching software has become an indispensable tool for many businesses regardless of size due to its ability to quickly detect discrepancies among large volumes of seemingly unrelated datasets with high accuracy rates–all while providing users with detailed insights into what may actually be going on behind the scenes at all times so that they can make informed decisions accordingly when necessary.
What Are Some Reasons To Use Data Matching Software?
Data matching software is a useful tool for businesses and organizations to store, access, and analyze data. Here are just a few reasons why data matching software should be used:
- Streamlines Data Storage: Data matching software helps streamline the process of storing and accessing large amounts of data by organizing them into more efficient datasets. This improved organizational structure makes it easier for users to quickly locate the exact data set they need without wasting time digging through multiple databases or folders.
- Automates Repetitive Tasks: By using automated processes, data matching software can quickly identify patterns in large datasets and filter out any irrelevant information with minimal manual input from users. This means that mundane tasks like cross-referencing lists or identifying duplicate accounts can be completed much faster than if done manually.
- Improves Analytics: By analyzing different sets of information simultaneously, data matching software can provide deeper insights regarding customer behaviors that wouldn’t have been visible if analyzed separately. This is especially helpful when dealing with larger quantities of data as the analysis becomes more accurate due to the increased number of samples being examined together.
- Enhances Security Measures: Businesses must remain compliant with security regulations when processing and storing sensitive customer data or risk facing legal repercussions from regulatory bodies such as GDPR or HIPAA. To achieve this, many utilize advanced algorithms within their data matching software which automatically flags potentially malicious activity such as suspicious logins or payments so that appropriate corrective measures can be taken immediately before any damage is done to the organization’s system.
Why Is Data Matching Software Important?
Data matching software is becoming increasingly important in this digital age due to the exponential growth of data. It allows organizations to quickly and accurately identify patterns and relationships between large volumes of data from a variety of sources. This in turn can help them understand customer behavior, reduce fraud, monitor compliance and improve operational efficiency.
Data matching software helps companies organize, store, analyze and make sense of the massive amounts of data that are out there today. With access to data across all channels, different departments within an organization can collaborate better when decisions about customers or potential new markets must be made. Powerful analytics tools have become available with the use of data matching software which allow businesses to gain valuable insights from their datasets that would have been impossible before.
Moreover, using data matching software enables organizations to protect sensitive information by detecting any fraudulent activity as it happens rather than after it has occurred. By continually monitoring trends over time with effective algorithms they are also able to spot red flags such as sudden changes in account status or usage indicating potentially suspicious behavior. As a result companies can be more secure by safeguarding against threats before they become costly security breaches or incidents.
In conclusion, with the ever-increasing amount of data being generated by people every day through their devices and applications combined with the need for better insights into customer behavior, analysis and fraud-detection capabilities; it is clear why data-matching software has become so important in recent years for businesses around the world.
Data Matching Software Features
- Pattern Matching: Pattern matching technology is used to find similar patterns between two different sets of data. This can be used to detect fraudulent activities or inaccurate information in databases.
- Data Reduction: Data reduction allows users to reduce the number of data points present in a database by eliminating duplicate, outdated, and irrelevant entries while maintaining the accuracy and completeness of the remaining dataset.
- Linkage Analysis: Linkage analysis is a process that involves cross-referencing and analyzing records from multiple sources simultaneously in order to identify relationships, trends, similarities, or discrepancies among them. This can help organizations detect fraud more quickly and accurately than other methods of screening for inaccuracies.
- Duplicate Record Detection: Duplicate record detection uses pattern matching or fuzzy logic algorithms to spot duplicate records within a database which could otherwise cause errors or inaccuracies if left unchecked.
- Standardization/Normalization: Standardization and normalization are both processes used by data matching software that reformat data into consistent formats so that it may be easily compared against other datasets without introducing differences due to formatting inconsistencies between them (e.g., date formats).
- Validation & Verification: Validation and verification are crucial components in any data matching system as they ensure accurate results by comparing inputted information against existing records for accuracy before it is entered into the main database for further use or comparison with other datasets.
Types of Users That Can Benefit From Data Matching Software
- Marketing Professionals: Data matching software can help marketing professionals identify potential customers and target them with campaigns that speak directly to their needs.
- Analysts: Analysts can use data matching tools to make informed decisions based on meaningful correlations between large datasets. These correlations may provide insights into trends and other factors that can be used to increase efficiency or drive sales.
- Data Scientists: Data scientists leverage data matching software to uncover hidden patterns in datasets and gain a clearer understanding of customer behavior. This insight can be used to refine product offerings, optimize campaigns, or meet customer demands more accurately.
- HR Professionals: HR professionals often need to identify duplicates in employee records, such as resumes and backgrounds checks in order to ensure successful onboarding processes. Data matching software makes this process faster and more accurate.
- Sales Teams: Sales teams use data matching technology for prospecting, contact acquisition, lead scoring, cross selling opportunities, and segmentation strategies for targeted outreach efforts designed to maximize ROI from each campaign or sale effort.
- Developers & Engineers:Developers and engineers use data matching tools to quickly locate errors in their code or databases by spotting differences between two inputs using pattern detection algorithms and quickly correcting any discrepancies encountered.
How Much Does Data Matching Software Cost?
The cost of data matching software can vary greatly depending on the features and capabilities included. Generally, most basic types of data matching software come with a one-time fee that ranges from hundreds to thousands of dollars. However, more comprehensive solutions may be priced on a subscription basis, meaning the cost is paid monthly or yearly and tends to be much higher than a one-time fee. Additionally, some companies may offer custom pricing for larger orders or special deals for nonprofits. Ultimately, the cost of data matching software will depend on what you need and how it fits into your budget.
Data Matching Software Risks
- Accuracy: Data matching software can be vulnerable to errors in its results due to the complexity of the data sets being analyzed and compared. Additionally, mistakes can occur during the input process (i.e. incorrect or incomplete data).
- Accessibility: If unauthorized people have access to the software or are able to view its results, it could lead to a breach of confidentiality or misuse of sensitive personal data.
- Security: Malicious users could use data matching software in order to commit fraud or identity theft if they gain access to secure networks and systems where such information is stored.
- Privacy: Poorly-designed data matching software may not protect individuals’ privacy rights, as it might collect more information than necessary and/or share that information with third parties without explicit consent from the individual concerned.
- Reliability: There is always a risk that the software may become outdated over time as technology advances (e.g., new algorithms for detecting patterns) and therefore should be regularly monitored for updates and improvements in order remain reliable.
What Software Can Integrate with Data Matching Software?
Data matching software can integrate with a variety of types of software. For example, marketing automation software such as email campaigns, customer data management solutions, CRM solutions, ERP solutions, and financial analytics tools can all be integrated with data matching software. Such integrations allow businesses to gain deeper insights into their customers and accurately target their audiences for personalized campaigns and promotions. In addition, many companies also use data mining software to feed into the data matching process so they can better understand patterns in customer behavior and develop strategies to better meet customer needs. Finally, warehouse management systems may also integrate with data matching software to ensure accurate inventory levels are maintained across multiple locations.
What Are Some Questions To Ask When Considering Data Matching Software?
- What kind of data formats does the software support?
- Does the software offer any de-duplication capabilities to identify matching records?
- Is there an option for fuzzy logic algorithms to match similar but not exact records?
- How user friendly is the interface for creating and running rules to match records?
- Are there different types of matching algorithms available (e.g., name, address, etc.)?
- Can you batch-process large datasets in a single pass or will it require multiple passes to complete the job?
- Does the software run on a centralized server platform or can it be distributed across multiple systems?
- What kind of security measures are in place to protect sensitive data during matching operations?
- Does the software provide data storage solutions so users don't have to manually store results outside of the application itself?
- What sort of scalability options are available for larger datasets and more complex needs?