Every business needs data to make business plans and directions, while poor quality data can lead to flawed analysis, inefficient operations, and missed business opportunities. Using data cleansing tools is a key factor to ensure data integrity and reliability. In this article, DIGI-TEXX, will provide an overview of the top data cleansing tools, from open-source solutions to comprehensive enterprise platforms.
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Tibco Clarity
Tibco Clarity is a part of the TIBCO ecosystem, integrated right into their data management solutions like TIBCO MDM and features within Spotfire. It’s a SaaS helper designed for data cleansing, letting users visually explore, profile, and clean up their data in an interactive way.
The thing that makes Clarity shine is its intuitive user interface. It makes exploring and understanding your data a breeze using charts and visuals. Clarity packs a punch with features like data profiling, sampling, rule-based validation, standardization, transformation, deduplication, address checks, and data mapping. One cool feature is the ‘transformation undo’ – super helpful for avoiding data errors. Users can pull in data from lots of different places and some popular formats: XLS, JSON, cloud storage, and data warehouses.
Clarity is a great fit if you love a visual, hands-on way to clean data, or companies are hunting for a solid cloud-based solution.
DemandTools
DemandTools, a tool from Validity – specifically built to be a powerhouse data cleansing tool right within Salesforce and Microsoft Dynamics 365 CRM environments. Think of DemandTools as the kind of data cleansing tool that integrates tightly with specific business apps or workspaces. It boosts the functionality within that ecosystem rather than trying to be a general, all-purpose cleaner.
DemandTools breaks down into three main modules, each tackling specific parts of the data cleansing process:
- Cleansing Tools: This is all about fixing errors and stopping duplicate data in its tracks using smart algorithms. It can even handle converting leads without accidentally creating copies.
- Discovery Tools: Use this to check CRM data against external sources, making sure everything is accurate and up-to-date.
- Maintenance Tools: This helps streamline everyday CRM data tasks like loading data, running reports, reassigning records, backing things up, and manipulating data.
So, who should use DemandTools? It’s perfect for companies and organizations already using Microsoft Dynamics 365 CRM or Salesforce CRM and looking to seriously boost their data quality within those platforms.
OpenRefine
OpenRefine (formerly known as Google Refine) is a free, open-source data cleansing tool that can run directly on the user’s computer. The strength of this tool is its combination of flexible processing capabilities, extensibility, and accessibility towards open source, creating a different solution than commercial data cleansing tools. With the ability to operate locally on the user’s platform, OpenRefine helps address data privacy concerns compared to cloud-based tools.
The main features of the tool focus on 7 steps, specifically as follows:
- Data conversion: OpenRefine supports data conversion between different formats.
- Data structuring: The tool ensures that data is clearly structured and consistent.
- Parsing: Extract data from online data sources via URL.
- Data exploration: OpenRefine uses facets to look at and filter data from multiple perspectives, acting more like a database than a spreadsheet.
- Clustering: The tool then applies clustering algorithms to find and merge similar but not identical values (e.g. misspellings, abbreviations), which helps solve data quality issues that simple rule-based systems cannot.
- Data linking: Finally, the tool connects and extends the dataset with external web services or links to cloud data sources.
- Infinite undo/redo: The tool also allows users to go back to any previous state of the dataset, so they can continue cleaning and extracting data until they are satisfied.
In general, OpenRefine is targeted at data analysts, librarians, scientists, and anyone working with data who needs something better than a standard spreadsheet, but is also suitable for businesses interested in processing locally on their infrastructure or looking for a cost-effective solution.
Trifacta Wrangler
Trifacta Wrangler is a data cleansing tool for the Alteryx platform and is integrated into the Alteryx Designer Cloud solution. Trifacta takes a more visual approach to data than other tools and stands out for its use of artificial intelligence (AI) to guide users through the interface, data cleansing, and transformation process. The integration into Alteryx reflects the Alteryx ecosystem’s focus on data preparation specifically for downstream analysis and modeling.
According to many users, Trifacta Wrangler is good at transforming, analyzing, and visualizing data. Its core strength is the application of machine learning (ML) to automatically suggest cleaning and structuring steps based on the data content. The tool then identifies anomalies, such as detecting inconsistencies, strange values, and other data quality issues. The tool also supports monitoring automation to automate overall data quality monitoring.
This data cleansing tool also has many versions to suit different scales, such as Wrangler, Pro, Enterprise; now the tool is integrated into Alteryx Cloud packages.
As described above, Trifacta Wrangler is suitable for data analysts, business users, and freelance teams working with data who prefer a visual, guided approach to data preparation and cleaning, especially those who are using or considering using the Alteryx ecosystem in their work.
Winpure Clean & Match
Winpure Clean & Match is a data cleansing tool that can be installed locally on the user’s computer. This tool focuses on cleaning and removing duplicates in business data and customer data, such as CRM lists and email lists.
Winpure Clean & Match also includes the basic features of a data cleansing tool, but it stands out in that it can work well with common databases and spreadsheets such as CSV, SQL Server, Oracle, Salesforce, Excel. Some of the features of Winpure are as follows:
- Clean & Normalize: Winpure will provide options to clean data structures, handle and add missing, inconsistent values, and normalize data according to pre-defined rules. The tool can also support cleaning by component (e.g. separating names, addresses).
- Data Matching & Deduplication: Winpure supports matching & fuzzy matching – to identify similar but not exactly identical data records that may be due to spelling or abbreviation errors. This feature is extremely useful for solving complex identification problems in customer data.
- Address Verification: Integrates global address verification and normalization capabilities based on the global address database.
- Profiling: The tool will also be able to help analyze and understand data quality issues before cleaning.
- Compatibility: Works well with a variety of databases and spreadsheets (, etc.).
Also a data cleansing tool with an intuitive, easy-to-use and no-code user interface, Winpure makes it easy for non-technical users to access. In addition, the tool also supports automation features to help schedule data cleaning and matching tasks more effectively. The tool also comes in different editions (Small Business, Pro Business, Enterprise, Server) and has a free trial period.
Winpure is suitable for businesses (especially SMEs), marketing teams, data analysts who work with customer data or regularly send Marketing emails based on CRM data (Salesforce, etc.), and users who need high accuracy in removing duplicates and verifying addresses.
Melissa Clean Suite
Melissa Clean Suite is a data cleansing tool designed as an add-on to integrate with leading CRM platforms such as Salesforce and Microsoft Dynamics CRM. Its core value lies in its deep integration, making data quality assurance part of the CRM workflow instead of a separate process from other tools.
In terms of features, Melissa stands out from other data cleansing tools in the following ways:
- Real-time verification: The tool can automatically verify and standardize contact information (address, email, phone number) at the time of data entry into CRM, preventing incorrect data from being entered into the system.
- Batch Cleaning: The tool supports the ability to clean and verify all existing data on CRM.
- Data Standardization & Auto-Completion: Melissa can standardize addresses in the postal format of more than 240 different countries and automatically complete addresses when entering data to speed up data processing.
- Deduplication: Similar to other tools, Melissa can also remove duplicate data values.
- Enrichment: The tool can use integrated technologies to add valuable information to customer profiles such as demographics and firmographics, set lead scoring and identify market segments. This positions Melissa not only as a data cleansing tool but also as an effective sales and marketing support tool.
Due to its strong integration with Salesforce and/or Microsoft Dynamics CRM for customer relationship management, the target audience of Melissa Clean Tool is businesses that are directly using these platforms or sales and marketing teams that use these platforms to improve data quality and campaign effectiveness.
RingLead
RingLead is a tool within the ZoomInfo platform. RingLead is not just a simple data cleansing tool but a comprehensive data orchestration tool, specifically designed for data in CRM and Marketing Automation systems. The tool is designed with a new approach, where data cleansing is one component of a larger strategy to optimize sales and marketing activities.
RingLead’s features are also very broad and versatile, meeting the basic needs of a data cleansing tool.
- Data quality: Cleanse data through normalization and deduplication, and link related records (e.g. link leads to existing contacts or accounts).
- Enrichment: The tool can also fill in missing information or update customer data from external sources similar to other data cleansing tools.
- Discovery: Helps identify and better understand existing data.
- Data orchestration: The tool can implement features such as segmentation, scoring, list building, routing, and prospecting.
As can be seen, the target audience of the tool is organizations looking for a comprehensive platform to manage, clean, enrich, and orchestrate their CRM and marketing automation data to improve sales and marketing performance.
Informatica Cloud Data Quality
Informatica Cloud Data Quality is a data cleansing tool within the Informatica Intelligent Data Management Cloud (IDMC), evolving into a comprehensive cloud data management platform. The tool acts as a powerful data cleansing tool and a self-service data quality management solution, powered by artificial intelligence (AI). Informatica was developed to embrace the idea that data quality is not a standalone function but an integral part of the intelligent data management era, emphasizing the role of data in supporting larger initiatives such as AI, analytics, and data governance.
Key features also include the basic features of a data cleansing tool: profiling, cleansing, standardization, enrichment, deduplication, and address verification. Other notable features include:
- AI-Driven: Leverage AI to automate critical tasks, detect data anomalies, make intelligent recommendations, and create data quality rules, helping to increase productivity and efficiency.
- Self-service: The tool can also empower business users and data analysts to self-manage data quality through an intuitive interface and pre-built rules, reducing dependence on IT.
- Cloud-Native: The tool is built on the cloud platform, providing flexible scalability for each need and high performance.
- Integration: As part of IDMC, the tool is seamlessly integrated with other Informatica services such as data integration, data governance and data catalog.
Informatica’s target audience is definitely organizations and companies of all sizes looking for a cloud-based, scalable data platform for data quality, governance and integration.
Oracle Enterprise Data Quality
Oracle Enterprise Data Quality (EDQ) is an enterprise-grade data quality management platform that can also serve as a general-purpose data cleansing tool. It is also designed to generate master data. EDQ’s position in the Oracle ecosystem shows that its main strength lies in data quality management for organizations that have invested heavily in the Oracle ecosystem.
EDQ supports a comprehensive set of tools for managing data quality throughout the lifecycle. It also includes the basic features of a data cleansing tool such as: profiling, standardization, matching & duplication, parsing, monitoring.
The special feature of EDQ is that it is designed to integrate into Oracle’s Siebel, E-Business Suite, Fusion Applications, supporting advanced features such as governance, integration, migration, MDM & BI.
EDQ is definitely suitable for organizations, especially medium and large enterprises, that are using Oracle platform applications or looking for an enterprise-class data governance platform to easily manage data quality and create master data.
SAS Data Quality
SAS Data Quality is a data cleansing tool that is part of the SAS Viya platform or it can also operate independently. SAS is a comprehensive data quality solution and a flexible data cleansing tool, featuring the ability to clean data directly at the data source. SAS is suitable for organizations with large data volumes, strict data storage requirements, or complex data processes where moving data to the infrastructure for cleaning is impractical or costly.
In addition to the basic features, SAS stands out with the following features:
- Source cleaning: Ability to clean data in many different environments: on-premise, cloud, hybrid, data lakes, relational databases—without moving data to the database.
- Cleaning functionality: Tools to support data profiling, normalization, deduplication, error correction, entity identification, and data remediation)
- Governance & Monitoring: SAS also integrates data governance, continuous data quality monitoring, MDM, business glossary
The tool will be suitable for businesses with multiple hybrid/multi-cloud data sources that need to perform data cleaning without moving a lot of data. Especially suitable for organizations that are using SAS for their analytics needs.
IBM Infosphere Information Server
IBM Infosphere Information Server is a comprehensive enterprise data management and integration platform, and can also be used as a high-level data cleansing tool. Similar to Oracle and Informatica, IBM positions itself in managing its data quality in a large platform, targeting enterprise-wide data management challenges.
Key features also include basic features such as profiling, source data investigation, deduplication, data monitoring & governance. In addition, the tool also has advanced features such as:
- Integration: Provides data transformation and near real-time integration.
- Scalability: Designed to scale data quality operations seamlessly as data needs increase. This, along with near real-time integration, makes it suitable for complex, big data environments where performance and scalability are critical.
IBM Cloud Pak is suitable for medium and large enterprises that need a comprehensive, integrated platform for data integration, data quality, and data governance.
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Conclusion
This article has reviewed the majority of data cleansing tools on the market, from flexible open source solutions like OpenRefine to CRM-specific tools like DemandTools and Melissa Clean Suite. As well as comprehensive enterprise data management platforms suitable for large organizations like Informatica, Oracle, SAS, and IBM. Choosing the right data cleansing tool is not a one-size-fits-all decision. This decision depends on many factors specific to each organization. If your organization is facing data quality challenges or looking to optimize data-driven processes, DIGI-TEXX is ready to accompany you as a partner providing professional data processing services.
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