10 Best Data Cleaning Services in 2023 [Updated]

Keeping your data tidy is no easy feat. With more data flowing into businesses today than ever before, it’s getting harder to stay on top of data quality and ensure your information is accurate and reliable. That’s where professional data cleaning services come in handy!

These companies specialize in detecting and fixing errors, inconsistencies, duplicates, and other data issues that can undermine analysis and decision making. Having clean, standardized data sets the stage for success with everything from reporting to AI projects.

In this post, I’ll share my top picks for data cleaning services to consider in 2023. These providers offer versatile options to suit different needs and budgets. Whether you’re looking to cleanse a customer database, product catalog, or other business information, these services can lend a hand.

I’ll cover key factors like data security, privacy, and pricing. You’ll also get a peek at each company’s cleaning capabilities and approach. Read on to discover the best data cleaning services that can save you time, effort, and headache in the new year!

What is Data Cleaning?

Let’s start with the basics – what is data cleaning anyway? Quite simply, it’s the process of fixing up your data so it’s nice and tidy.

See, when data comes flowing into your systems from different sources and processes, it can easily end up with errors, inconsistencies, and other issues. Maybe customer addresses are entered inconsistently. Product names are spelled in different ways. Important fields are left blank. Transactions get duplicated. You get the idea.

Data cleaning tackles these problems head-on so your data is squeaky clean. It involves steps like filling in missing info, standardizing formats, deleting duplicate entries, and checking for errors. The goal is to get your data in shape so you can actually use it.

Common data cleaning tasks include:

  • Removing duplicate records
  • Fixing incorrect or invalid entries
  • Standardizing formats like dates and names
  • Deleting irrelevant information
  • Checking data against reliable sources

With quality data that’s cleaned up, you can get accurate insights from analytics and reports. It also prepares data to work seamlessly with business intelligence, machine learning, and other important initiatives. So don’t underestimate the power of tidying up your data!

Best Data Cleaning Services

When data’s dirty, you gotta clean it up. Luckily, some great services can lend a hand with tidying up your info. Here are my top picks for data cleaning heroes to call on in 2023:

#1. OpenRefine – Data Cleaning Services

OpenRefine - Data Cleaning Services
OpenRefine – Data Cleaning Services

Once called Google Refine, OpenRefine is a free, open source warrior that battles messy data to whip it into shape. This powerful tool cleans, reconciles, and transforms both small and gigantic data sets with ease.

Some of OpenRefine’s cleansing superpowers include:

  • Identifying duplicate entries and resolving differences
  • Standardizing formats and fixing errors
  • Parsing unwieldy text into columns
  • Adding, removing and rearranging columns
  • Clustering like data for editing in bulk
  • Integrating and matching data from multiple sources

You can also use OpenRefine to easily transform data from one format into another. That comes in handy when importing data into other apps.

The best part? As an open source tool, OpenRefine is totally free to use and even modify. So you can customize it to fit your data cleaning needs. This free and mighty data hero is ready to tidily vanquish any dirty data dragon!

#2. Trifacta Wrangler

Trifacta Wrangler
Trifacta Wrangler

Brought to you by the makers of Data Wrangler, Trifacta Wrangler is an interactive data tidying tool. It helps analysts and data scientists clean and transform messy, complex data with less time wasted on formatting.

Some of Trifacta Wrangler’s best features:

  • Quickly standardizes diverse data sets
  • Machine learning suggests useful transformations
  • Handles large data volumes with ease
  • Interactive interface for on-the-fly cleaning
  • Focuses analysis on high-value data prep

Trifacta Wrangler comes with smarts to do the heavy lifting. Its machine learning algorithms recommend transformations and aggregations to apply based on the data. This allows you to spend less time on repetitive formatting tasks.

For pricing, Trifacta Wrangler offers a free basic version. The Pro version costs $419 monthly per user and adds more data prep features. Large enterprises can get custom pricing for the Enterprise version.

#3. Drake

Drake a data cleaning

Drake breezes through repetitive data prep work thanks to its straightforward text-based workflow. It lets you define a series of data processing steps, inputs and outputs. Drake then handles dependency resolution and executes commands in the optimal order.

Some key features that make Drake a data cleaning dynamo:

  • Automates matching, merging, and transforming data
  • Plain text configuration for easy setup
  • Determines command order based on data dependencies
  • Adds, deletes, and moves columns with ease
  • Machine learning rapidly processes large volumes

Drake was designed specifically for streamlined data workflow management. By organizing commands around the data itself, Drake works smarter not harder when cleaning your info.

The best part? Drake is free and open source. That means you can access its data cleaning superpowers without any cost. This free tool will whip your data into shape in no time!

#4. Tibco Clarity

Tibco Clarity

Get a better view of your messy data with Tibco Clarity, a visual interactive data cleaning platform. It streamlines discovering, profiling, and fixing data issues so information is analysis-ready.

Tibco Clarity’s user-friendly interface lets you:

  • Visually inspect data as you cleanse
  • Perform deduplication to remove copies
  • Standardize international address data
  • Enrich data by merging sources
  • Employ validation rules to catch errors
  • Smooth ETL process via seamless integrations

Advanced machine learning algorithms also help Tibco Clarity correct data inconsistencies automatically.

By processing raw data through Tibco Clarity, you get high-quality cleansed data prepared for analytics and other applications. Interactive visual tools give you control over the cleansing process from start to finish. Tibco Clarity brings a clear view to any dirty data job.

#5. PurifyData

PurifyData. affordable data cleansing service

Get your data squeaky clean and lead generation popping with PurifyData. Our affordable data cleansing service whisks away errors, inconsistencies, and duplicates so you can make spot-on business decisions.

Our three-step cleansing process includes:

  1. Data Assessment – We audit your data to find errors, fill gaps, and identify fixes.
  2. Data Cleaning – We thoroughly clean your data by fixing typos, removing duplicates, standardizing formats and more.
  3. Data Validation – We thoroughly validate the data has no remaining issues and check it against statistical tests.

And the cost? Our competitive rates start at an affordable $4 per hour. Curious to learn more? Try our data cleansing service for free on your first small project!

With clean and complete data, PurifyData also boosts your lead generation. Our qualified leads convert to customers at proven higher rates.

Stop wrestling with dirty data – let PurifyData clean it up at a reasonable price! Our experts make it fast and easy to unlock quality business insights.

#6. Winpure


Winpure works wonders at removing data dirt quickly and affordably. It cleans massive volumes from CRMs, databases, spreadsheets, and more with advanced features.

Some of Winpure’s top talents:

  • Lightning-fast scrubbing of big data
  • Eliminates duplicates and standardizes formats
  • Corrects errors with fuzzy matching
  • Multi-language version available
  • Versatile integration and customization

Winpure offers a free basic version plus paid editions:

  • Small business: $999
  • Medium/Large business: $1999
  • Enterprise pricing customized

For an all-in-one solution at a reasonable price, Winpure can’t be beat. It whisks away massive data dirt while matching quality standards. Put Winpure’s cleaning powers to work for pristine data at a cost that fits your business.

#7. DemandTools


Get your CRM data in tiptop shape with DemandTools. This suite is purpose-built to cleanse and enrich contact data in Salesforce, Microsoft Dynamics, and other CRMs.

DemandTools is the go-to for contextual B2B data cleansing with features like:

  • Dupe prevention for crisp databases
  • Automated lead enrichment
  • Smart parsing and standardization
  • Targeted matching across sources
  • seamless CRM integrations

Pricing starts at $1200 base charge for up to 10 users, plus $120 per additional user. A free 5-day trial is available.

For companies relying on CRM data, DemandTools is the specialist for accurate and complete information. It delivers the quality contact data needed to optimize sales and marketing performance.

#8. Quadient Data Cleaner

Quadient Data Cleaner

Data Cleaner from Quadient is a free and powerful open source tool for deep data profiling and quality analysis. It helps uncover hidden patterns, inconsistencies, and other issues so you can start cleansing.

Some of Data Cleaner’s top features:

  • Statistical analysis to detect data issues
  • Fuzzy logic duplicate identification
  • Custom validation rules
  • Data monitoring over time
  • Data masking for sensitive info

The community version of Data Cleaner is free to use. For full-scale deployments, pricing is available upon request based on your business needs.

Data Cleaner gives you an X-ray view inside your dirty data so you can target cleansing where it matters most. Its analytical capabilities help create the foundation for high quality, reliable data.

#10. Reifier


Reifier by Aficx brings the power of machine learning to tackle your biggest and messiest data. It uses Spark for rapid distributed data processing along with proprietary algorithms.

Some of Reifier’s standout features:

  • High-performance fuzzy matching
  • Machine learning for data improvements
  • Distributed processing for large data sets
  • Flexible deployment options
  • Continuous data monitoring

Reifier can handle tasks like deduplication, data merging, and record linkage with precision and speed. Its distributed architecture easily scales.

Pricing is customized based on each business’s unique data needs and infrastructure. The Aficx team will discuss requirements to provide tailored solution pricing.

For heavyweight data transformation jobs, Reifier delivers advanced machine learning with scalability. It enables automated and continuous data cleansing even as new data flows in.

Importance of Data Cleaning in an ETL Process

In any ETL (Extract, Transform, Load) pipeline, data cleaning plays a crucial role. It’s a foundational step that sets the stage for success.

ETL processes pull data from different sources, transform it, and load it into a destination system for reporting, analytics, etc. The “transform” portion is where data cleaning comes into play.

Here are some reasons why cleansing in ETL is so important:

  • Removes errors that can lead to inaccurate analysis and metrics.
  • Standardizes data from diverse sources into consistent, compatible formats.
  • Improves data integrity for reliable downstream use.
  • Enables joins/merges between data sources.
  • Saves compute resources by deleting unused data.
  • Prepares data to work well with EDW, data lakes, BI tools, etc.
  • Fixes faulty data that could break ETL process.

Data cleaning is the foundation for valuable, trustworthy data pipelines. It improves data quality before moving and loading data into target systems. Investing in robust data cleaning safeguards the reliability of the full ETL workflow.

Limitations of Using Data Cleaning Services

While data cleaning services provide many perks, some drawbacks exist:

  • Basic services may improperly clean complex data scenarios. Advanced logic and oversight is needed.
  • Pricier services are out of reach for many budgets. Free versions skimp on capabilities.
  • Security risks when exposing sensitive data to third parties.
  • Time-consuming process, especially for large datasets. Requires patience.
  • Results may need monitoring and occasional re-cleansing as new data flows in.


Maintaining pristine data is crucial for today’s data-driven businesses. Professional cleaning services can save time and effort on improving data hygiene.

Consider important factors like data security, scalability for large volumes, and capabilities before choosing a solution. Basic services may fall short on complex needs. High-end options get costly.

Set realistic expectations on turnaround times as well. Data cleaning takes patience, especially first passes on messy data. Plan for occasional refreshing as new data comes in.

With the right cleansing service and pragmatic expectations, businesses can tap into the true value of their data assets. Clean data leads to accurate analytics fueling good decisions.

For optimal results, explore end-to-end solutions like Hevo Data for automated data integration, cleansing, and management. Removing ETL burdens lets you focus on core priorities.

What are data cleansing services?

Data cleansing services help fix inconsistencies, errors, duplicates, and other issues in datasets through processes like standardization, validation, and deduplication. The goal is to improve quality and reliability of data.

How much does data cleansing cost?

Costs vary widely based on service, features, and data volume. DIY open source tools are free. Basic cloud services start around $10/month. Full-service options cost over $1000+ monthly. Costs also depend on one-time vs ongoing plans.

What does data cleansing do?

Data cleansing improves data quality by:
Finding and removing errors
Filling in missing values
Standardizing formats
Deleting unnecessary data
Checking against authoritative sources
Removing duplicate entries
This makes data more accurate and useful for analysis.

What are the methods of data cleaning?

Correction – Fixing errors and typos
Completion – Filling in missing data
Verification – Checking data against reliable sources
Consolidation – Merging duplicate records
Standardization – Formatting data consistently
Filtering – Removing irrelevant data
The best approach depends on the specific data issues that need addressing.

Leave a Comment