How to Remove Enter from Data in SQL Server: Remove Newlines, Carriage Returns, and Whitespace Efficiently 2026

How to remove enter from data in sql server: you’ll learn quick, practical ways to strip newline characters Enter/CR/LF and unwanted whitespace from strings stored in SQL Server. Quick fact: removing hidden line breaks can drastically improve data presentation and downstream processing. Here’s a practical guide you can follow end-to-end:

• Quick fix: use REPLACE to strip newline characters CHAR13 and CHAR10.
• Cleaner data: combine TRIM or LTRIM/RTRIM with REPLACE to purge leading/trailing spaces.
• Practical patterns: update existing records, or select clean data on the fly with computed columns or CTEs.
• Real-world tips: handle mixed line breaks, tabs, and multiple consecutive newlines to normalize text fields.

Quick references useful URLs and Resources
Apple Website – apple.com
Artificial Intelligence Wikipedia – en.wikipedia.org/wiki/Artificial_intelligence
SQL Server Documentation – devblogs.microsoft.com
SQL Server Transact-SQL Reference – learn.microsoft.com
Stack Overflow – stackoverflow.com

Understanding the Problem: Where Do Enter Characters Hide?

Enter characters are typically CR Carriage Return, CHAR13 and LF Line Feed, CHAR10. Windows text files often use a CRLF pair, while Unix-based systems use LF alone. In databases, these characters can sneak into:

• Product descriptions
• Notes fields
• Customer feedback
• Logs or audit trails

When you pull data into reports or export to CSV, visible line breaks can wreck layouts, break parsing, or cause lookups to misbehave. So the goal is to normalize or remove them where appropriate.

Basic Replacement Techniques

Remove CR, LF, or Both

• Remove CR Char13 only: UPDATE t SET col = REPLACEcol, CHAR13, ”
• Remove LF Char10 only: UPDATE t SET col = REPLACEcol, CHAR10, ”
• Remove both CR and LF: UPDATE t SET col = REPLACEREPLACEcol, CHAR13, ”, CHAR10, ”

Remove All Whitespace Around the Text

• Trim spaces from both ends SQL Server 2017+: UPDATE t SET col = LTRIMRTRIMcol
• If you need to trim more aggressively, combine with REPLACE to squeeze internal extra spaces:
  UPDATE t SET col = REPLACELTRIMRTRIMcol, ‘ ‘, ‘ ‘
  Note: this only reduces double spaces; you might loop or use a function for multiple passes.

Normalize Internal Line Breaks to a Space

• Normalize to a single space between words:
  UPDATE t SET col = REPLACEREPLACEREPLACEcol, CHAR13, ‘ ‘, CHAR10, ‘ ‘, ‘ ‘, ‘ ‘
  Repeat as needed to collapse multiple spaces.

Practical Example: Clean a Description Field

• Step 1: Remove CR and LF
  UPDATE Products SET Description = REPLACEREPLACEDescription, CHAR13, ”, CHAR10, ”
• Step 2: Trim edges
  UPDATE Products SET Description = LTRIMRTRIMDescription
• Step 3: Normalize internal whitespace
  UPDATE Products SET Description = REPLACEDescription, ‘ ‘, ‘ ‘
  You may need to loop this step a few times if you have many consecutive spaces.

Using Functions for Reusability

Create a Simple Function to Strip CR/LF

CREATE FUNCTION dbo.fn_RemoveEnter@text NVARCHARMAX
RETURNS NVARCHARMAX
AS
BEGIN
SET @text = REPLACEREPLACE@text, CHAR13, ”, CHAR10, ”;
SET @text = LTRIMRTRIM@text;
— collapse multiple spaces
WHILE CHARINDEX’ ‘, @text > 0
SET @text = REPLACE@text, ‘ ‘, ‘ ‘;
RETURN @text;
END
GO

Use the Function in Queries

SELECT dbo.fn_RemoveEnterDescription AS CleanDescription
FROM Products;

Update Table with a Function

UPDATE Products
SET Description = dbo.fn_RemoveEnterDescription; How to Recover a Deleted Table in SQL Server: Restore, Undelete, Backups, and Point-In-Time Techniques 2026

Handling Tabs and Other Invisible Characters

Remove Tabs CHAR9

UPDATE t SET col = REPLACEcol, CHAR9, ”

Remove All Invisible Control Characters

CREATE FUNCTION dbo.fn_StripControlChars@text NVARCHARMAX
RETURNS NVARCHARMAX
AS
BEGIN
DECLARE @i INT = 1;
DECLARE @len INT = LEN@text;
DECLARE @out NVARCHARMAX = ”;

WHILE @i <= @len
BEGIN
DECLARE @ch NCHAR1 = SUBSTRING@text, @i, 1;
IF @ch NOT IN CHAR9, CHAR10, CHAR13, NCHAR0
SET @out = @out + @ch;
SET @i = @i + 1;
END
RETURN @out;
END
GO

— Then apply:
UPDATE t SET col = dbo.fn_StripControlCharscol;

Notes: How to Ping a Server Port Windows Discover the Easiest Way to Check Your Connection 2026

• This approach may be slower on very large tables; consider batching or using a staging table for massive cleans.
• For Unicode data, ensure the functions use NVARCHAR and NCHAR to preserve characters.

Working with Large Texts: Performance Tips

• Batch updates: UPDATE t SET col = … WHERE id BETWEEN @start AND @end
• Use computed columns for on-the-fly cleanliness without data changes
• If you need to keep original data, add a new cleaned column and populate it, then swap in latest

Real-World Scenarios and Examples

Scenario 1: Cleaning Product Descriptions Before Export

• Problem: Several rows contain CRLF and multiple spaces
• Solution: A small update script to clean data and a view to export cleaned data
  CREATE VIEW vCleanProducts AS
  SELECT ProductID, dbo.fn_RemoveEnterDescription AS CleanDescription, Price
  FROM Products;

Scenario 2: Normalizing Customer Notes for Search

• Goal: Remove line breaks so notes are in a single paragraph for better search indexing
• Approach: Use a function to replace CR/LF with spaces and compress spaces
  UPDATE Customers
  SET Notes = dbo.fn_RemoveEnterdbo.fn_StripControlCharsNotes;

Scenario 3: Data Migration: Normalize Text During Migration

• When moving data between systems, apply the cleansing function in the ETL step
  • In SSIS, use a Script Task to apply the function
  • In SQL, use a staging table to hold cleaned data before final insert

Validation and Verification

Quick Checks after Cleaning

• Count line breaks remaining:
  SELECT SUMLENcol – LENREPLACEcol, CHAR13, ” AS CR_Count,
  SUMLENcol – LENREPLACEcol, CHAR10, ” AS LF_Count
  FROM t;

• Check for double spaces:
  SELECT COUNT* FROM t WHERE col LIKE ‘% %’;

• Spot-check a sample:
  SELECT TOP 10 col FROM t WHERE col LIKE ‘%’ + CHAR10 + ‘%’ OR col LIKE ‘%’ + CHAR13 + ‘%’;

Data Quality Metrics to Track

• % of fields cleaned
• Reduction in visible line breaks per row
• Time per cleaning batch
• Post-clean validation pass rate

Performance-Considerate Alternatives

Use a View for Surface-Level Cleanliness

If you don’t want to change data, create a view that returns cleaned results:
CREATE VIEW vCleanedProducts AS
SELECT ProductID, dbo.fn_RemoveEnterDescription AS Description, Price
FROM Products;

Use APPLY for On-the-Fly Cleansing During Joins

SELECT p.ProductID, a.CleanNotes
FROM Products p
CROSS APPLY SELECT dbo.fn_RemoveEnterNotes AS aCleanNotes; How To Populate Your Discord Server The Ultimate Guide 2026

Best Practices

• Test on a non-production copy first to gauge performance
• Keep a backup before mass updates
• Use functions with NVARCHAR to support Unicode data
• Consider user-facing implications: if you remove line breaks in user content, ensure readability in downstream systems

Quick Reference: Common Commands

• Remove CR and LF from a column:
  UPDATE t SET col = REPLACEREPLACEcol, CHAR13, ”, CHAR10, ”;

• Trim spaces:
  UPDATE t SET col = LTRIMRTRIMcol;

• Normalize internal spaces:
  UPDATE t SET col = REPLACEcol, ‘ ‘, ‘ ‘;

• Create a reusable remover function:
  see function code above

Common Pitfalls

• Over-removal: stripping all whitespace can make text hard to read
• Performance: large tables may require batching
• Mixed newline formats: ensure you cover CR, LF, and CRLF variations
• Unicode issues: use NVARCHAR/NCHAR in all steps

Comparison: Manual vs. Automated Cleansing

• Manual approach: quick fix for small datasets, but error-prone and hard to repeat
• Automated approach: consistent results, auditable steps, scalable to big data

Maintenance and Extensibility

• Add tests to your data-cleaning routine to ensure new edge cases are covered
• Document the function logic and update scripts for future changes
• Consider adding a versioned cleaning pipeline to rollback if needed

Frequently Asked Questions How to pass parameters to view in sql server 2008: Parameterized Views, TVF, and Best Practices 2026

How do I remove Enter characters from a string in SQL Server?

Use REPLACE to strip CR and LF: UPDATE t SET col = REPLACEREPLACEcol, CHAR13, ”, CHAR10, ”.

Can I remove all whitespace from a string?

You can trim edges with LTRIMRTRIMcol and replace multiple spaces with a single space, though removing all whitespace inside strings can make text unreadable.

How do I normalize line breaks in a column that has mixed CRLF formats?

Strip both CHAR13 and CHAR10 and replace with a single space if you want to keep words together.

Is there a built-in function for removing newline characters?

SQL Server doesn’t have a direct single function for “remove newlines”; combining REPLACE with CHAR13 and CHAR10 is the standard approach.

Should I use a function or inline SQL for cleaning?

For reusability and readability, a function is preferable. Use inline SQL if you only need one-off updates. How to open a port in windows server 2026 firewall: Inbound rules, ports, and security best practices

How can I apply cleansing during data migration?

Apply the cleansing function in your ETL process or use a staging table to ensure only cleaned data lands in the destination.

How do I remove tabs from a string?

REPLACEcol, CHAR9, ” will remove tab characters.

How can I preserve data while cleaning?

Backup your data first, then create a cleaned copy or a view that presents cleaned data without altering the original.

How many times should I run the whitespace normalization loop?

Run until no double spaces remain, which usually requires 1–3 iterations depending on data quality.

How can I verify the cleaning worked?

Run sanity checks: count CR/LF occurrences, look for remaining double spaces, and spot-check a sample of cleaned rows. How to Name Query a Specific DNS Server: DNS Query Targeting, DNS Server Selection, Dig NSLookup Examples 2026

Yes, you can remove enter from data in SQL Server by replacing CR and LF characters with nothing. In this guide, you’ll get a practical, battle-tested approach to cleaning newline characters from VARCHAR and NVARCHAR fields, plus tips on handling whitespace, Unicode line terminators, and large datasets without tanking performance. We’ll cover simple one-liners, more robust batch updates, and reusable patterns you can drop into ETL pipelines or daily maintenance jobs. Think of this as a toolbox: pick the right tool for the job, whether you’re cleaning a single column or an entire table.

Useful URLs and Resources:

• Microsoft Docs – learn.microsoft.com/sql/t-sql/functions/replace-transact-sql
• Microsoft Docs – learn.microsoft.com/sql/t-sql/functions/translate-transact-sql
• Microsoft Docs – learn.microsoft.com/sql/t-sql/functions/char-transact-sql
• Microsoft Docs – learn.microsoft.com/sql/t-sql/functions/ltrim-transact-sql
• SQL Server Blog – sqlservercentral.com
• SQLShack – sqlshack.com
• Stack Overflow – stackoverflow.com/questions/tagged/sql-server

Introduction: quick-start snapshot

• What you’ll learn: how to remove CR carriage return and LF line feed characters from data, when to use REPLACE vs TRANSLATE, and how to do it safely on large datasets.
• Format you’ll see: step-by-step commands, real-world examples, performance notes, and validation checks.
• Outcome: clean strings free of unwanted newline characters, with options to preserve or remove surrounding spaces as needed.

Why newline characters show up in SQL Server

• Text data often comes from user inputs, external feeds, or exports that embed CR/LF sequences CHAR13 and CHAR10.
• On Windows, the standard newline is CRLF two characters: \r and \n. Some sources use just CR or just LF.
• If you’re exporting to CSVs, rendering in reports, or storing free-form notes, those newlines can cause formatting issues or break downstream parsing.

Key characters to know How to Mute Someone in a Discord Server A Step by Step Guide 2026

• Carriage Return CR: CHAR13
• Line Feed LF: CHAR10
• Windows newline: CR + LF CHAR13 + CHAR10
• Unicode line terminators you might encounter in some data: NEL U+0085, CRLF sequence in NVARCHAR content, etc.

Basic one-liner cleanup: remove CR and LF

• The simplest approach is to strip CR and LF from a string with nested REPLACE calls.
• Example: update a single table column
  • update dbo.Notes
    set NoteText = REPLACEREPLACENoteText, CHAR13, ”, CHAR10, ”;
• If you also want to remove leading/trailing whitespace after cleaning, you can wrap with LTRIM/RTRIM or TRIM SQL Server 2017+.

Code block: simple CR/LF removal

UPDATE dbo.Notes
SET NoteText = REPLACEREPLACENoteText, CHAR13, '', CHAR10, '';

When to use TRANSLATE for bulk cleanup

• TRANSLATE is great when you’re removing a set of single-character replacements in one pass.
• It’s available since SQL Server 2017, and it can be faster than repetitive nested REPLACE calls for multiple characters.

Code block: using TRANSLATE to drop CR and LF

UPDATE dbo.Notes
SET NoteText = TRANSLATENoteText, CHAR13 + CHAR10, '';

Removing all whitespace vs just newlines How to Open SQL Server in Visual Studio 2017 A Step by Step Guide: Connect, LocalDB, SSDT 2026

• If your goal is to collapse all whitespace spaces, tabs, newlines into nothing, you can use TRANSLATE to strip a broader set of characters, or apply a more involved pattern with PATINDEX and a loop.
• For most cases, you’ll want to remove newlines first, then decide about spaces. If you want to remove all whitespace including spaces, consider replacing with an empty string in batches or using a function for reuse.

Code block: remove CR/LF and then trim spaces

UPDATE dbo.Notes
SET NoteText = LTRIMRTRIMREPLACEREPLACENoteText, CHAR13, '', CHAR10, '';

Advanced: removing all whitespace with TRANSLATE spaces, tabs, newlines

• If you’re on SQL Server 2017+, you can strip a wide range of whitespace by translating them to nothing in one pass.

UPDATE dbo.Notes
SET NoteText = TRANSLATENoteText, ' \t\r\n', '';

• Note: This example removes spaces, tabs, and CR/LF. If you need to preserve certain spaces e.g., between words, adjust the translation set accordingly.

Handling NVARCHAR and Unicode

• For NVARCHAR data, use N” literals for Unicode safety when you need to specify literal characters.
• Example explicit: replace CRLF in NVARCHAR column

UPDATE dbo.Notes
SET NoteText = REPLACEREPLACE NoteText, NCHAR13, N'', NCHAR10, N'';

• In practice, the same REPLACE/TRANSLATE approach works for NVARCHAR; just ensure your literals are Unicode if you’re including characters beyond ASCII.

Cleaning multiple columns in one go

• When cleaning several columns in the same table, you can repeat the same pattern for each column, or build a small dynamic SQL block to apply to a set of target columns.
• For a safe, straightforward approach, run separate UPDATE statements for each column during a maintenance window.
• If you want to automate, you can use a simple script to generate UPDATE statements for a list of columns.

Code block: batch-clean multiple columns manual approach
/* Example for a table with three text columns */
UPDATE dbo.Notes
SET NoteText = REPLACEREPLACENoteText, CHAR13, ”, CHAR10, ”; How to protect a Discord server from raids: the ultimate guide 2026

UPDATE dbo.Notes
SET AuthorNote = REPLACEREPLACEAuthorNote, CHAR13, ”, CHAR10, ”;

UPDATE dbo.Notes
SET Summary = TRANSLATESummary, CHAR13 + CHAR10, ”;

Performance considerations: updates on large tables
- Cleanups can lock rows and cause long transactions. Use batched updates.
- Recommended approach: update in small chunks using a key, increasing a progress column, or using TOP in a loop.
- Example of batched approach:

DECLARE @Rows int = 1;
WHILE @Rows > 0
BEGIN
UPDATE TOP 1000 dbo.Notes
SET NoteText = REPLACEREPLACENoteText, CHAR13, ”, CHAR10, ”
WHERE NoteText LIKE ‘%’ + CHAR13 + ‘%’ OR NoteText LIKE ‘%’ + CHAR10 + ‘%’;
SET @Rows = @@ROWCOUNT;
END

- Benefits: reduces lock contention, keeps log usage predictable, and minimizes impact on concurrent users.
- Don’t forget to monitor your transaction log during big cleanups; consider enabling minimal logging practices where possible e.g., using simple recovery model in test environments, if appropriate.

Validation and verification
- After cleanup, it’s essential to verify there are no remaining CR/LF characters in the target columns.
- Quick check:

SELECT COUNT* AS RowsWithCRLF
FROM dbo.Notes
WHERE NoteText LIKE ‘%’ + CHAR13 + ‘%’ OR NoteText LIKE ‘%’ + CHAR10 + ‘%’;

- If you’re using TRANSLATE to remove a broader set of whitespace and you want to confirm, run a similar query for the absence of any characters in the translation set.
- Consider adding a post-cleanup check in your automated tests or data quality pipelines.

Edge cases to watch out for
- Mixed encodings: Data imported from varied sources may use non-breaking spaces or other Unicode spaces. You may need to extend the characters you remove.
- Data integrity: Some fields use newline characters intentionally e.g., formatted notes. In those cases, you might want to remove only at the end of lines or replace sequences with a single space.
- Data type constraints: If the column is not VARCHAR/NVARCHAR but another type, convert to string via CAST/CONVERT or handle in ETL steps before updating.
- Backups: Always back up before performing mass in-place updates, especially on production systems.
- Trimming side effects: If you remove CR/LF inside a meaningful structure like structured logs, ensure you don’t break formatting.

Real-world examples and use-cases
- Contact notes stored by users sometimes include extra lines; cleaning makes search and analytics more reliable.
- Export pipelines that feed customer support dashboards benefit from removing newline noise.
- Content moderation pipelines often normalize text before keyword matching; consistent newline handling helps.

Best practices and patterns you can reuse
- Use REPLACE for a small, targeted set of characters, especially when you only need to remove CR/LF.
- Use TRANSLATE when you have multiple characters to replace in a single pass for performance.
- For large tables, prefer batched updates with clear commit points to minimize locking and log growth.
- Normalize data after cleaning e.g., trim extra spaces, fix casing if needed to keep data quality high.
- Maintain a small, reusable function if you apply the cleanup in many places:

CREATE FUNCTION dbo.fn_RemoveNewlines @s NVARCHARMAX
RETURNS NVARCHARMAX
AS
BEGIN
RETURN TRANSLATEREPLACE@s, CHAR13, ”, CHAR10, ”
END How to Mask SSN Data in SQL Server: Dynamic Data Masking, Encryption, and Best Practices 2026

- Then use in your UPDATEs:

UPDATE dbo.Notes
SET NoteText = dbo.fn_RemoveNewlinesNoteText;

Measuring success: what counts as “clean”
- No CR/LF present in the cleaned columns.
- Whitespace not in unwanted places depending on your rules — for example, no empty lines unless required by formatting.
- Downstream processes search, indexing, export work without misformatted lines or broken records.

Troubleshooting tips
- If you don’t see changes, check for hidden Unicode characters beyond CR/LF, such as NEL or LINE SEPARATOR U+2028, U+2029. You may need to extend the translation set.
- If performance tanks, try batching more aggressively or running the update during low-traffic windows.
- If applications rely on newline characters for specific formatting, consider replacing them with a standard single space instead of removing entirely.

Performance benchmarks rough guidelines
- Simple CR/LF removal on a 10 MB text column is usually nearly instantaneous on modern SQL Server hardware.
- On multi-GB tables, expect CPU and I/O to influence duration; batching is essential.
- TRANSLATE tends to be faster for removing multiple single-character tokens compared to nested REPLACE calls.
- Always test in a staging environment with a realistic data sample to estimate production impact.

Frequently asked questions
# What does CRLF stand for?
CRLF stands for Carriage Return CR and Line Feed LF. It’s the two-character sequence used as the Windows newline.

# How do I remove only CR characters from a column?
Use: UPDATE table SET column = REPLACEcolumn, CHAR13, ''; If you also want to remove LF, include a second REPLACE for CHAR10.

# How do I remove only LF characters from a column?
Use: UPDATE table SET column = REPLACEcolumn, CHAR10, ''; If you also want to remove CR, include a second REPLACE for CHAR13.

# Can I remove CR and LF from NVARCHAR data without losing Unicode safety?
Yes. Use NVARCHAR literals and Unicode-aware functions, e.g., UPDATE table SET column = REPLACEREPLACEcolumn, NCHAR13, N'', NCHAR10, N''; or TRANSLATE with Unicode inputs.

# Should I remove spaces along with newlines?
That depends on your data needs. If you want to remove spaces as well, apply an additional REPLACE for ' ' or use TRANSLATE to target a broader set of whitespace characters.

# What’s the difference between TRIM and REPLACE for this task?
TRIM removes leading and trailing whitespace, not internal CR/LF. REPLACE or TRANSLATE removes CR/LF and possibly other whitespace from anywhere in the string.

# How can I remove CRLF in place for many rows efficiently?
Batch updates are key. Use TOP with a loop to process a fixed number of rows at a time, commit, then proceed to the next batch. This minimizes locking and log usage.

# How do I validate the cleanup after running the update?
Run a query to count rows that still contain CR or LF. If the count is zero, you’re clean. Also, run sample exports or downstream checks to confirm formatting is as expected.

# Can I reuse cleanup logic across multiple tables?
Yes. Create a scalar function e.g., dbo.fn_RemoveNewlines or a CROSS APPLY pattern to apply the same transformation across different columns, then reuse across scripts and jobs.

# Are there any gotchas with Windows vs Unix line endings?
Yes. Windows uses CRLF, Unix uses LF only. If you’re consolidating data from cross-platform sources, your cleanup should handle both cases CR, LF, or CRLF to avoid leaving orphaned characters.

# How do I handle data that must preserve certain newline structures?
If there’s business logic requiring newlines in specific fields, selectively replace only the unwanted patterns for example, replace CRLF with a single space, or remove extra blank lines while keeping the first newline. This keeps formatting where it’s intentionally used.

# Is there a way to automate this in ETL pipelines without touching production directly?
Absolutely. Integrate a cleaning step in your ETL workflow SSIS, Azure Data Factory, or custom ETL scripts to apply REPLACE/TRANSLATE during data ingestion, ensuring downstream tables are clean at the point of load.

Conclusion
- Clean and consistent data makes search, reporting, and downstream integrations much more reliable.
- Start with CR/LF removal using REPLACE or TRANSLATE, then extend to broader whitespace as needed.
- Use batched updates for large tables, validate thoroughly, and consider reusable functions to streamline future cleanups.

Frequently Asked Questions continued
# Can I test cleanup changes on a copy of production data?
Yes. Always test on a staging copy or a subset of data to verify behavior before applying to production.

# What about cleaning in a view or computed column?
You can apply CLEAN logic in a view or computed column, but keep in mind that performance may vary. Materialized results may require periodic refresh.

# How do I preserve newline formatting guaranteed for human readability while still cleaning data?
Replace CR/LF with a single space or a single newline if you need readability rather than removing entirely. Example: replace CRLF with a single space: UPDATE t SET c = REPLACEREPLACEc, CHAR13, '', CHAR10, ' ';

# Are there built-in best practices for naming cleanup functions?
Name them clearly, e.g., dbo.fn_RemoveNewlines or dbo.fn_CleanTextWhitespace. Include the scope in the name if you plan to reuse across many tables e.g., fn_CleanText_TextColumn.

# How can I monitor ongoing cleanup jobs?
Log progress in a control table, track row counts per batch, and set up alerts if batch duration exceeds thresholds. Consider auditing after completion to confirm no CR/LF remnants.

# Can I clean data in-place from an application layer as a first pass?
Yes, for user-generated content this is common. However, enforce a server-side cleanup policy to ensure consistency across all data entry points.

# What’s the recommended approach for historical data that must remain unaltered?
For historical records, use a targeted cleanup strategy on new or active data, or store a clean copy in a separate column or archive table, preserving the original as-is.

# How do I handle columns with very large text VARCHARMAX / NVARCHARMAX?
The same techniques apply, but performance and temp storage may be more critical. Consider chunked processing and testing on representative large samples.

# Are there tools that help visualize newline cleanup impact?
Yes. Use data profiling tools, SSMS query plans, and lightweight dashboards to compare pre- and post-cleanup row counts, data lengths, and downstream error rates.



# Sources:



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