Tools that clean or correct data by getting rid of typos, formatting errors, and unnecessary and expendable data are known as data quality tools. These tools help organizations implement rules, automate processes, and remove costly inconsistencies in data to improve revenue and productivity.
Why is Data Quality Important?
The success of many businesses today is impacted by the quality of their data, from data collection to analytics. As such, it is important for data to be available in a form that is fit for use to ensure a business is competitive.
Quality data produces insights that can be trusted, reducing the waste of organizational resources and, therefore, impacting the efficiency and profitability of an organization. Maintaining high data quality standards also helps organizations satisfy different local and international regulatory requirements.
How do Data Quality Tools Work?
Data quality tools analyze information to identify obsolete, ambiguous, incomplete, incorrect, or wrongly formatted data. They profile data and then correct or cleanse data using predetermined guidelines with methods for modification, deletion, appending, and more.
Best Data Quality Tools & Software
DemandTools is a versatile and secure data quality software platform that allows users to speedily clean and maintain customer relationship management (CRM) data. It also provides users with correct report-ready data that boosts the effectiveness of their revenue operations.
- Data Quality Assessment: Through the Asses module, DemandTools helps users recognize the degree of strength or weakness of their data to determine where they should focus remediation efforts. Unactionable, Insufficient, Limited, Acceptable, and Validified are five data quality categories which allow users to understand the overall state of their data.
- Duplicate Management: DemandTools helps its customers to discover, remove, and prevent duplicate records from misleading various teams within the organization, thus complicating their customer journeys. Duplicate management happens through modules such as Dedupe, which cleans up existing duplicates; Convert, which keeps lead queues duplicate-free; and DupeBlocker, which is a Salesforce duplicate blocker.
- Data Migration Management: DemandTools ensures the integrity of data is maintained as it enters and exits Salesforce. It uses modules such as Import, Export, Match, Delete, and Undelete.
- Email Verification: Users can verify email addresses in their CRM to ensure they have an effective line of communication with their customers. And lead and contact email addresses can be verified in bulk.
Con: A majority of the tool is designed around Salesforce.
Pricing: Base pricing begins at $10 per CRM license. You can contact the vendor for a personalized quote.
Openprise is a no-code platform that empowers users to automate many sales and marketing processes to reap the value of their revenue operations (RevOps) investments. As a data quality tool, Openprise allows users to cleanse and format data, normalize values, carry out deduplication, segment data, and enrich and unify data.
- Openprise Data Cleansing and Automation Engine: Openprise ensures data is usable for users’ key systems through aggregation, enrichment, and transformation of data. Openprise’s focus goes beyond sales systems to offer flexibility to their customers. Integration with users’ marketing and sales systems enables Openprise to push clean data and results to these systems to deliver greater value.
- Openprise Bots: Users can deploy automated bots to monitor and clean data in real time to ensure data is always in the best condition.
- Normalized Field Values: Data is normalized to customers’ specifications to smoothen segmentation and reporting. It standardizes company names, phone numbers, and country and state fields among others.
- Deduplication: Users can dedupe contacts, accounts, and leads. It has prebuilt recipes designed involving best practices users can take advantage of. They can also modify dedupe logic to customize the deduplication process to their needs.
Con: The user interface (UI) can be overwhelming, especially to new users.
Pricing: The Professional package starts at $24K per year for up to 250K records. For the Enterprise package and further pricing information, contact Openprise.
RingLead is a cloud-based data orchestration platform that takes in data from many sources to enrich, deduplicate, segment, cleanse, normalize, and route. The processes help to enhance data quality, set off automated workflows, and inform go-to-market actions.
- RingLead Cleanse: RingLead Cleanse detects and removes duplicates in users’ data through proprietary duplicate merging technology. Users can clean CRM and marketing automation data through deduplication of people, contacts, leads, etc. RingLead Cleanse can also link people to accounts, normalize data structure, segment data into groups, and get rid of bad data.
- RingLead Enrich: The purpose of RingLead Enrich’s data quality workflow engine is to be the central point of users’ sales and marketing technology stack. Users can configure batch and real-time enrichment into their sales and marketing and data operations workflows. They can also integrate their internal systems and data ingestion processes with third-party data sources, optimizing ROI from third-party data enrichment.
- RingLead Route: Users can achieve validation, enhancement, segmentation, normalization, matching, linking, and routing of new leads, accounts, opportunities, contacts, and more in one flow, making RingLead a fast and accurate lead routing solution.
Con: The UI has a learning curve.
Pricing: Contact RingLead for custom pricing information.
Melissa Data Quality Suite
Melissa Data Quality Suite combines address management and data quality to ensure businesses keep their data clean. Melissa’s data quality tools clean, rectify, and verify names, phone numbers, email addresses, and more at their point of entry.
- Address Verification: Users can validate, format, and standardize the addresses of over 240 countries and territories in real time to prevent errors such as spelling mistakes, incorrect postal codes and house numbers, and formatting errors.
- Name Verification: Global Name identifies, genderizes, and parses more than 650K ethnically diverse names using intelligent recognition. It can also differentiate between name formats from different languages and countries and can parse full names, handle name strings, and flag vulgar and fake names.
- Phone Verification: Melissa Global Phone can validate callable phone numbers, determine their accuracy for the region, and verify and correct phone numbers at their point of entry to ensure users populate their databases with correct information. It also ensures the numbers are live and identifies the dominant languages in numbers’ regions.
- Email Verification: To prevent blacklisting and high bounce rates and to improve deliverability and response rates, Melissa Global Email Verification carries out email checks to fix and validate domains, spelling, and syntax. It also tests the SMTP (Simple Mail Transfer Protocol) to globally validate email addresses.
Cons: Address updates could be more frequent, and address validation can be resource-intensive and time-consuming.
Pricing: Base pricing is at $750 per year for 50K address validations. Contact Melissa for a free quote.
Talend Data Quality ensures trusted data is available in every type of integration, effectively enhancing performance and bettering sales while reducing costs. It enriches and protects data and ensures data is always available.
- Intuitive Interface: Talend Data Quality cleans, profiles, and masks data in real time, using machine learning to support recommendations for handling data quality matters. As a result, its interface is intuitive, convenient, and self-service, making it effective for not only technical but also business users.
- Talend Trust Score: The built-in Talend Trust Score provides users with instant, explainable, and actionable evaluations of confidence to separate cleansed datasets from those that need more cleansing.
- Talend Data Quality Service (DQS): With Talend DQS, organizations with limited data quality skills, talent, and resources can implement data quality best practices up to three times as fast as they would have by themselves. Talend DQS is a managed service that helps users constantly monitor and manage their data at scale as well as track and visualize data quality KPIs (key performance indicators).
- Asset Protection and Compliance: To protect personally identifiable information (PII) from unauthorized individuals, Talend Data Quality allows users to selectively share data with trusted users.
Cons: It can be memory-intensive.
Pricing: Contact Talend Sales for more information on pricing.
WinPure Clean & Match
WinPure Clean & Match carries out data cleansing and data matching to improve the accuracy of consumer or business data. This data quality tool features cleaning, deduplicating, and correcting functions ideal for databases, CRMs, mailing lists and spreadsheets among others.
- WinPure CleanMatrix: WinPure CleanMatrix gives users an easy yet sophisticated method to carry out numerous data cleaning processes on their data. It is divided into seven parts, with each part responsible for a data cleansing task.
- One-Click Data Cleaning Mode: Clean & Match has a one-click data cleaning feature that processes all the clean options across various columns simultaneously.
- Data Profiling Tool: The data profiling tool scans each data list and gives more than 30 statistics. It uses red and amber to highlight potential data quality issues like dots, hyphens, and leading or trailing spaces. These issues can be fixed with a single click.
Cons: It has a learning curve.
Pricing: It features a free version, but base pricing starts at $999 per license for one desktop for the Small Business package. For Pro Business and Enterprise packages, contact the vendor.
How the Data Quality Tools Compare
|Data Quality Tool
|Salesforce data, CRM
|Multiple data sources
|CRM, marketing automation data
|Melissa Data Quality Suite
|Talend Data Quality
|Data standardization, deduplication, validation, and integration
|WinPure Clean & Match
|Multiple data sources
Choosing a Data Quality Tool
Before selecting a data quality tool for your use case, it is important to consider your data challenges. Implementing a solution that partly or barely addresses your data challenges results in ineffective data management initiatives and impacts overall business success.
It is also important to understand the scope and limits of data quality tools to ensure they are effective. You should also consider the differentiators and weaknesses of the tools in consideration and align them with your goals. Finally, use free trials and demos where available for a hands-on experience.
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