How to extract date from date in sql server step by step guide: Master CAST, CONVERT, and DATEPART for clean dates 2026

How to extract date from date in sql server step by step guide. Quick fact: Removing the time portion from a datetime or datetime2 value is a common task to group, compare, or display dates only. In this guide, you’ll get a step-by-step approach, practical examples, and real-world tips to make date extraction in SQL Server a breeze. We’ll cover the core functions, common pitfalls, performance considerations, and a few handy patterns you can reuse in your day-to-day queries. Use this as your reference whenever you need to work with date-only data in SQL Server.

• Quick fact: You often need just the date part for reporting, grouping, or comparisons, ignoring the time.
• In this guide, I’ll walk you through how to pull the date from a datetime/datetime2/date value using simple, reliable methods.
• What you’ll get:
  • Step-by-step methods to extract the date
  • When to use each method CAST, CONVERT, FORMAT, DATEFROMPARTS, and more
  • Performance guidance and edge-case notes
  • Practical examples you can copy-paste
• Useful resources unlinked text only: SQL Server documentation – docs.microsoft.com; SQL Server DATEADD function – en.wikipedia.org/wiki/Date_and_time; Stack Overflow threads on extracting date in T-SQL.

What does “extracting the date” mean in SQL Server?

• In SQL Server, date/time values are stored with a date part and optionally a time part.
• The goal is to produce a value that contains only the calendar date year, month, day without any time component.
• Supported data types: datetime, smalldatetime, datetime2, date, and datetimeoffset. Each behaves a bit differently when you strip time, so pick the method that matches your type.

Core methods to extract just the date

1. CASTdate/time to date

• Best for: When you want to convert any date/time type to a pure date value.
• Syntax: CASTyour_column AS date
• Example:
  • SELECT CASTorder_date AS date AS order_date_only FROM Orders;
• Pros: Simple, clear, index-friendly if you have a date column.
• Cons: If you’re targeting older SQL Server versions, ensure compatibility.

2. CONVERT with style 112 or style yyyymmdd

• Best for: When you need a date string in a specific format or just a date without time in string form.
• Syntax: CONVERTdate, your_column or CONVERTvarchar10, your_column, 112
• Example:
  • SELECT CONVERTdate, order_date AS order_date_only FROM Orders;
  • SELECT CONVERTvarchar10, order_date, 112 AS order_date_string FROM Orders;
• Pros: Explicit format control for strings.
• Cons: If you need a date type, prefer CAST/CONVERT to date rather than varchar.

3. DATEFROMPARTS with DATEs

• Best for: Creating a new date from components useful if you’re manipulating year, month, day separately.
• Syntax: DATEFROMPARTSyear, month, day
• Example:
  • SELECT DATEFROMPARTSYEARorder_date, MONTHorder_date, DAYorder_date AS order_date_only FROM Orders;
• Pros: Guarantees a valid date; avoids time component entirely.
• Cons: Requires you to have or derive year, month, day parts.

4. DATEADD and DATEDIFF trick when needed

• Best for: Getting date boundaries or normalizing to midnight for comparisons.
• Examples:
  • Normalize to midnight for datetime2/datetime: SELECT DATEADDday, 0, DATEDIFFday, 0, order_date AS order_date_midnight FROM Orders;
  • Remove time by subtracting time portion: SELECT DATEADDsecond, -DATEDIFFsecond, CASTorder_date AS date, order_date, order_date AS order_date_only FROM Orders;
• Pros: Useful for windowing and precise midnight normalization.
• Cons: Less readable for just extracting date; can be overkill.

5. FORMAT function for strings, not ideal for performance

• Best for: When you need a specific string presentation, not for date math.
• Syntax: FORMATyour_column, ‘yyyy-MM-dd’
• Example:
  • SELECT FORMATorder_date, ‘yyyy-MM-dd’ AS order_date_string FROM Orders;
• Pros: Flexible formatting.
• Cons: Slower than CAST/CONVERT; not recommended for large datasets or performance-critical paths.

Which method should you use?

• If you just need a date value no time for comparisons, aggregations, or joins: CASTyour_column AS date or CONVERTdate, your_column.
• If you need a string, pick CONVERT with a style or FORMAT with caution on performance.
• If you’re manipulating components: DATEFROMPARTS is clean and safe.
• For performance-critical paths with large datasets, prefer CAST/CONVERT DATE rather than FORMAT.

Practical examples by data type

1. From a datetime column

• Table: Eventsevent_time datetime
• Goal: Get the date part only
• Query:
  • SELECT CASTevent_time AS date AS event_date FROM Events;
  • — or —
  • SELECT CONVERTdate, event_time AS event_date FROM Events;

2. From a smalldatetime column

• Table: Appointmentsapp_dt smalldatetime
• Query:
  • SELECT CASTapp_dt AS date AS appt_date FROM Appointments;

3. From a datetime2 column

• Table: Logslog_ts datetime27
• Query:
  • SELECT CASTlog_ts AS date AS log_date FROM Logs;

4. From a date column no time

• Table: Holidaysholiday_date date
• Query:
  • SELECT holiday_date AS holiday_date FROM Holidays;
  • Note: This is already date type; no extraction needed.

5. Extract date and compare date ranges real-world pattern

• Goal: Find orders placed on 2024-05-01
• Query:
  • SELECT * FROM Orders WHERE CASTorder_date AS date = ‘2024-05-01’;
  • Better: Use date range for performance:
  • SELECT * FROM Orders WHERE order_date >= ‘2024-05-01’ AND order_date < ‘2024-05-02’;
• Why preferred: Sargability—can use an index on order_date.

6. Group by date

• Goal: Count orders per day
• Query:
  • SELECT CASTorder_date AS date AS order_date_only, COUNT* AS orders_count
    FROM Orders
    GROUP BY CASTorder_date AS date
    ORDER BY order_date_only;

7. Index considerations

• If you frequently group or filter by date only, consider:
  • Creating a persisted computed column: ALTER TABLE Orders ADD order_date_only AS CASTorder_date AS date PERSISTED;
  • Then index that column: CREATE INDEX idx_order_date_only ON Ordersorder_date_only;
• Alternative: Use a date-dimension table for heavy BI workloads and join against it for performance.

Edge cases and gotchas

• Time zones: If your datetime values are in UTC or another timezone, consider converting to the target timezone first, then extract date. Example:
  • SELECT CASTSWITCHOFFSETorder_date, ‘-05:00’ AS date AS local_date FROM Orders;
  • Or with AT TIME ZONE:
  • SELECT CASTorder_date AT TIME ZONE ‘UTC’ AT TIME ZONE ‘America/New_York’ AS date FROM Orders;
• Leap seconds and ambiguous times: SQL Server handles datetime types with internal precision; using CAST to date drops time, no ambiguity remains.
• Performance with large tables: Avoid FORMAT for bulk operations. Use CAST/CONVERT to date for speed.
• Null values: If your column can be NULL, your CAST/CONVERT will return NULL accordingly; consider ISNULL/CODING for default dates if needed.

Date formats and string outputs

• To return a date string in ISO format yyyy-MM-dd:
  • SELECT CONVERTvarchar10, order_date, 23 AS order_date_iso FROM Orders;
• To return a compact numeric date yyyymmdd:
  • SELECT CONVERTvarchar8, order_date, 112 AS order_date_yyyymmdd FROM Orders;
• To format with dashes and a weekday not recommended for storage, only display:
  • SELECT FORMATorder_date, ‘yyyy-MM-dd ddd’ AS date_with_weekday FROM Orders;

Common mistakes to avoid

• Using GETDATE for static values: If you compare a stored date to today, remember to strip time properly, otherwise you’ll miss rows.
• Casting in WHERE clause without an index: This can disable index seeks. Prefer using a range predicate that leverages the underlying column’s index or add a persisted computed column as shown.
• Overusing FORMAT in large queries: It’s convenient but slow. Reserve FORMAT for presentation layers.

Performance tips and best practices

• Prefer date data type for new columns to simplify date-only operations.
• If you must work with datetime in a WHERE clause, consider rewriting to range predicates:
  • order_date >= @startDate AND order_date < DATEADDday, 1, @startDate
• Use a date-only computed column with a persistent option if you frequently filter by date-only values.
• Test performance on representative data volumes; what works in small datasets may stall in production.

Data and statistics industry-friendly context

• In a recent benchmark of SQL Server operations, queries that used CAST/CONVERT to date ran about 2x faster than FORMAT-based date extraction on large datasets.
• For BI workloads, using a star schema with a dedicated Date dimension dramatically improves query performance for date-based grouping and filtering.

Examples in a practical workflow

• You’re a data analyst pulling daily sales totals:
  • Step 1: Normalize order_date to date
  • Step 2: Group by the date
  • Step 3: Aggregate sales
  • SQL:
    • SELECT CASTorder_date AS date AS sale_date, SUMtotal_amount AS daily_sales
      FROM Orders
      GROUP BY CASTorder_date AS date
      ORDER BY sale_date;
• You’re building a daily report API:
  • Use a parameterized date range using the performance-friendly approach:
  • SELECT CASTorder_date AS date AS order_date, COUNT* AS orders
    FROM Orders
    WHERE order_date >= @start AND order_date < DATEADDday, 1, @end
    GROUP BY CASTorder_date AS date;

Table of quick references

• CASTyour_column AS date -> returns date-only value
• CONVERTdate, your_column -> returns date-only value
• DATEFROMPARTSyear, month, day -> constructs a date from components
• FORMATyour_column, ‘yyyy-MM-dd’ -> returns a formatted string less preferred for large datasets

From the trenches: common real-world patterns

• Pattern A: Date boundary filter without time
  • WHERE order_date >= ‘2024-01-01’ AND order_date < ‘2024-02-01’
• Pattern B: Date conversion for display in a report
  • SELECT CONVERTvarchar10, order_date, 120 AS order_date_display
• Pattern C: Creating a derived date column in a warehouse scenario
  • ALTER TABLE Orders ADD order_date_only AS CASTorder_date AS date PERSISTED;
  • CREATE INDEX idx_order_date_only ON Ordersorder_date_only;

Performance testing tips

• Compare two approaches on a representative sample:
  • A: SELECT CASTorder_date AS date FROM Orders WHERE CASTorder_date AS date = ‘2024-05-01’;
  • B: SELECT order_date FROM Orders WHERE order_date >= ‘2024-05-01’ AND order_date < ‘2024-05-02’;
• Measure execution time, logical reads, and execution plan to decide the best path.

Advanced topics

• Time zone-aware date extraction:
  • SELECT CASTorder_time AT TIME ZONE ‘UTC’ AT TIME ZONE ‘America/Los_Angeles’ AS date AS local_date FROM Orders;
• Handling historical data with changing time zones or daylight saving adjustments by standardizing on a single time zone or using a date dimension table.

Best practices for teaching and sharing

• Use clear, incremental examples that readers can run and adapt.
• Include side-by-side comparisons code snippets to show what changes when switching methods.
• Keep performance notes in the margin so users don’t choose slow methods by habit.

Frequently Asked Questions

What does it mean to extract date from date in sql server step by step guide?

Extracting the date means returning a value that contains only the calendar date, ignoring any time component, using functions like CAST or CONVERT.

Which method is fastest for getting a date from a datetime?

CASTyour_column AS date or CONVERTdate, your_column are typically faster and more index-friendly than FORMAT.

Can I keep the time zone information when extracting dates?

If you need to preserve time zone context, first convert to a specific time zone with AT TIME ZONE, then extract the date.

How do I extract date for grouping without losing performance?

Use a CAST/CONVERT to date in the SELECT and GROUP BY, or create a persisted computed column and index it.

Should I use DATEFROMPARTS?

DATEFROMPARTS is great when you’re building a date from separate year, month, and day values or when you want a guaranteed valid date.

How do I format the date as a string?

Use CONVERT with a style code e.g., 23 for yyyy-mm-dd or FORMAT for flexible formatting. FORMAT is slower for large datasets.

How do I filter by a specific date range efficiently?

Use a range predicate that leverages the index, like order_date >= ‘2024-01-01’ AND order_date < ‘2024-01-02’.

What about smalldatetime?

CASTsm_datetime AS date works, similar to datetime. The time portion is truncated.

Is there any difference between CAST and CONVERT for date?

For converting to a date type, both are effective; CAST is more standard SQL, CONVERT offers style options for strings.

Can I extract the date as a time zone-aware value?

Yes, with AT TIME ZONE before extracting the date to normalize to a reference time zone.

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If you’re building a video around this, consider outlines like:

• Quick intro with the most common use-cases
• Live coding of converting a datetime column to date
• Side-by-side performance test: CAST vs FORMAT vs DATEFROMPARTS
• Real-world scenarios: daily sales, event logs, date dimension
• FAQ recap and best practices

Further reading and references unlinked text:

• SQL Server Documentation
• SQL Server DATE and TIME Functions
• Datetime vs Date Data Types in SQL Server
• Best practices for indexing date columns in SQL Server
• Common SQL patterns for date-based reporting

Extract the date portion from a datetime in SQL Server by using CASTyourColumn AS DATE or CONVERTDATE, yourColumn. In this guide, you’ll learn a straightforward, step-by-step approach to pulling out the date, handling different data types, and avoiding common pitfalls. We’ll cover practical examples, best practices, and performance tips. You’ll also see how to format dates for display, filter by date ranges, and optimize queries that rely on date extraction. Here’s what you’ll get:
– A clear step-by-step process you can apply today
– Real-world examples for common data types DATE, DATETIME, DATETIME2, SMALLDATETIME
– Quick-reference tables comparing date/time types and their storage
– Pitfalls to avoid like index usage when filtering by date
– Tips for formatting, time zones, and performance
Useful URLs and Resources:
– Microsoft Docs – docs.microsoft.com
– SQL Server Central – sqlservercentral.com
– Stack Overflow – stackoverflow.com
– Wikipedia – en.wikipedia.org/wiki/Date_and_time

Introduction to date extraction in SQL Server

When you’re dealing with dates and timestamps in SQL Server, you often want just the date part year-month-day without the time component. This is especially true for reporting, daily aggregations, or when you’re targeting a specific day in a large dataset. The two most common ways to extract the date part are:

– CASTcol AS DATE
– CONVERTDATE, col

This section walks you through why these methods matter, the exact syntax, and how they behave across different date/time data types.

Why this matters for performance and accuracy
– Using DATE alone saves storage and is faster for comparisons and grouping.
– Casting or converting to DATE strips away time, which is essential for daily aggregations.
– Be mindful of time zones if your data stores time in UTC or with offset. you may need to convert before extracting the date.

Understanding date-related data types in SQL Server

Here’s a quick, practical overview of the main date/time types you’ll encounter, with a focus on how date extraction works for each:

– DATE: Stores a date only range: 0001-01-01 to 9999-12-31. Uses 3 bytes. Perfect for birthdates, anniversaries, or any date-only value.
– TIMEp: Stores time of day with optional precision p 0-7. Range 00:00:00.0000000 to 23:59:59.9999999.
– DATETIME: Stores date and time, with precision about 3.33 milliseconds. Range 1753-01-01 to 9999-12-31. Uses 8 bytes.
– SMALLDATETIME: Stores date and time with lower precision minutes. Range 1900-01-01 to 2079-06-06. Uses 4 bytes.
– DATETIME2p: Stores date and time with user-defined precision p 0-7. Range 0001-01-01 to 9999-12-31. Uses 6-8 bytes depending on precision.
– DATETIMEOFFSETp: Like DATETIME2 with an offset preserved for time zone awareness. Range 0001-01-01 to 9999-12-31 with offsets from -14:00 to +14:00.

Key takeaway: If you only need the date portion, DATE is the simplest and most efficient type to work with going forward.

Step-by-step guide: how to extract date from a date column

Follow these steps to reliably extract the date portion from a datetime-like column and keep your queries fast and readable.

Step 1: Identify the date column
– Locate the column in your table that contains date/time data e.g., order_date, event_timestamp.
– Determine its data type DATE, DATETIME, DATETIME2, SMALLDATETIME. This matters for how you’ll handle formatting and indexing.

Step 2: Basic date extraction with CAST
– Use CAST to strip the time portion and return a DATE value.
– Example:
SELECT CASTorder_timestamp AS DATE AS order_date_only
FROM orders.

Step 3: Basic date extraction with CONVERT
– CONVERT offers a similar approach and is often used when you also need style codes for string output.
SELECT CONVERTDATE, event_time AS event_date
FROM events.

Step 4: When to prefer CAST vs CONVERT
– CAST is simpler and often clearer. CONVERT is helpful if you need to apply a style when converting to a string e.g., for display or when you’re working with legacy code.
– Examples:
SELECT CASTshipment_date AS DATE AS shipment_date
FROM shipments.
SELECT CONVERTDATE, shipment_time AS shipment_date

Step 5: Grouping and filtering by date without hurting indexes
– For grouping by date, cast in the SELECT and GROUP BY, but be mindful of index usage.
– For filtering by a specific date range on large tables, avoid applying a function directly to a column in the WHERE clause if it blocks index seeks.
– Good approach for filtering a range on a datetime column:
SELECT *
FROM logs
WHERE log_time >= ‘2026-01-01’ AND log_time < ‘2026-01-02’.
– If you must extract date for filtering, consider using an indexed computed column or a persisted computed column:
ALTER TABLE logs ADD log_date AS CASTlog_time AS DATE PERSISTED.
CREATE INDEX IX_logs_log_date ON logs log_date.
— Then:
WHERE log_date = ‘2026-01-01’.

Step 6: Handling NULLs and data quality
– If your date/datetime column can be NULL, always consider how that affects your downstream logic.
SELECT COALESCECASTevent_time AS DATE, ‘1900-01-01’ AS event_date
– Better yet, handle NULLs in your application logic and keep the database clean with constraints where appropriate.

Step 7: Working with DATETIME2 and precision
– When you’re extracting the date from a DATETIME2 column, CAST or CONVERT to DATE behaves the same way, but you’ll preserve precise storage in the underlying column.
SELECT CASTorder_time AS DATE AS order_date
FROM orders_datetime2.

Step 8: Time zone considerations
– If your data uses time zones, convert to the desired zone before extracting the date.
– Example simplified:
SELECT CASTorder_utc_time AT TIME ZONE ‘UTC’ AT TIME ZONE ‘Pacific Standard Time’ AS DATE AS order_pst_date

Step 9: Formatting dates for display
– If you need a string representation, FORMAT is flexible but slower. prefer CONVERT with style codes on strings when possible.
SELECT CONVERTVARCHAR10, CASTorder_time AS DATE, 120 AS date_iso
SELECT FORMATorder_time, ‘yyyy-MM-dd’ AS date_string

Step 10: Best practices and hygiene
– Prefer DATE type for date-only fields going forward.
– Keep time information in DATETIME23 or higher if you need precision, and strip time only when you’re ready to display or group by date.
– Index date-related columns. consider computed columns if you frequently group or filter by the date portion.

Practical examples and quick references

Sample data and common scenarios to keep handy:

– Scenario: Get the date part from a DATETIME column for daily sales totals
– SQL:
SELECT CASTsale_time AS DATE AS sale_date, SUMamount AS total_sales
FROM sales
GROUP BY CASTsale_time AS DATE
ORDER BY sale_date.

– Scenario: Filter records from a date only perspective without losing index efficiency
SELECT *
FROM events
WHERE event_time >= ‘2026-02-01’ AND event_time < ‘2026-02-02’.

– Scenario: Ensure no time part when comparing dates across systems
FROM users
WHERE CASTbirthdate AS DATE = ‘1990-05-21’.

– Scenario: Convert to a date string for reporting
SELECT CASTorder_date AS VARCHAR10 AS order_date_str
FROM orders.

– Scenario: When storing dates, switch to DATE to save space
ALTER TABLE customers ADD signup_date DATE.

Table: date/time types at a glance storage and use cases

| Data Type | Typical Use Case | Storage | Date Range |
|—————|————————————–|———|——————————–|
| DATE | Date-only values | 3 bytes | 0001-01-01 to 9999-12-31 |
| TIMEp | Time of day only | 5-16 bytes depending on p | 00:00:00.0000000 to 23:59:59.9999999 |
| DATETIME | Date and time, legacy support | 8 bytes | 1753-01-01 to 9999-12-31 |
| SMALLDATETIME | Date and time with minute precision | 4 bytes | 1900-01-01 to 2079-06-06 |
| DATETIME2p | Precise date and time, modern use | 6-8 bytes | 0001-01-01 to 9999-12-31 |
| DATETIMEOFFSETp | Date/time with time zone offset | 8-9 bytes | 0001-01-01 to 9999-12-31 with offset -14:00 to +14:00 |

Tip: For new designs, prefer DATE and DATETIME2 with appropriate precision for better performance and future-proofing.

Best practices for date extraction and querying

– Use DATE for date-only logic and filtering whenever possible.
– Avoid applying functions to a column in a WHERE clause if you can restructure the predicate to preserve index seeks.
– Consider adding a persisted computed column for the date portion if you frequently filter or group by the date, then index that column.
– When working with time zones, normalize to a common zone typically UTC before extracting the date portion for reporting.
– Use appropriate string formats only for display. keep data in date/time types for calculations and comparisons.
– Document your date conventions in your data dictionary to prevent confusion between date-only fields and date-time fields.

Real-world scenarios and performance tips

– Aggregation by date on large datasets
– Use a persisted computed column for the date portion and index it to speed up GROUP BY operations.
– Example:
ALTER TABLE orders ADD order_date_only AS CASTorder_time AS DATE PERSISTED.
CREATE INDEX IX_orders_order_date_only ON orders order_date_only.
– Filtering by a date range for dashboards
– Prefer range-based filters on the datetime column itself to keep index usage:
WHERE event_time >= @startDate AND event_time < DATEADDDAY, 1, @startDate.
– Handling historical data
– If you have mixed data types, convert on the read path and store consistently for outputs:
SELECT CASTevent_time AS DATE AS event_date, COUNT FROM events GROUP BY CASTevent_time AS DATE.

Troubleshooting: common mistakes to avoid

– Mistake: Using WHERE CASTdate_col AS DATE = ‘2026-02-01′ on large tables
– Why it’s bad: Casting on the column can prevent index usage, slowing down queries.
– Fix: Use a range predicate on the original column, or create a persisted date column as a filter key.
– Mistake: Relying on string comparison for dates
– Why it’s bad: It’s locale-sensitive and error-prone. always use proper date types for logic.
– Fix: Keep dates as DATE or DATETIME/DATETIME2 as long as possible. cast only when needed for display.
– Mistake: Mixing time zones without a standard
– Why it’s bad: Offsets can cause off-by-one-day errors.
– Fix: Normalize to UTC, then extract the date.

Frequently Asked Questions

# 1. How do I extract only the date from a DATETIME column?
You can use CASTyourColumn AS DATE or CONVERTDATE, yourColumn. For example:
SELECT CASTorder_time AS DATE AS order_date FROM orders.

# 2. Can I extract the date from a string that looks like a date?
Yes, but you should first parse the string into a date type, then extract the date. Example:
SELECT CAST’2026-03-15 12:34:56′ AS DATETIME AS dt, CASTCAST’2026-03-15 12:34:56’ AS DATETIME AS DATE AS only_date.

# 3. What’s the difference between DATE and DATETIME2 for new projects?
DATE stores only the date portion, uses less storage and is ideal for dates without time. DATETIME2 stores date and time with higher precision and a larger range. it’s generally preferred when you need precise time data or want to future-proof with flexible precision.

# 4. How do I extract the date from a DATETIME2 column?
Use the same approach as with DATETIME: CASTdatetime2_column AS DATE or CONVERTDATE, datetime2_column.

# 5. How can I format a date for display in a specific format?
Use FORMAT easy but slower or CONVERT to a string with a style code. Examples:
SELECT FORMATorder_time, ‘yyyy-MM-dd’ AS date_str.
SELECT CONVERTVARCHAR10, CASTorder_time AS DATE, 120 AS date_str_iso.

# 6. How do I group by date when I have timestamps?
Cast to date in both SELECT and GROUP BY:
SELECT CASTorder_time AS DATE AS order_date, COUNT FROM orders GROUP BY CASTorder_time AS DATE.

# 7. What should I do to optimize queries that extract date from a large table?
Create a persisted computed column for the date portion, then index that column. This helps preserve index seeks while keeping the date logic intact.

# 8. Is there a performance difference between CAST and CONVERT for date extraction?
Performance is generally similar for both when just extracting a date. CAST is more concise. CONVERT is useful if you later need string styles or compatibility with older code.

# 9. How do I handle time zones when extracting dates?
If your data uses UTC or offsets, convert to the target time zone first using AT TIME ZONE and then extract the date.

# 10. Can I extract the date portion during data loading or ETL?
Yes. Normalize to the date during ETL, store as DATE, and only convert to strings for reports.

# 11. How do I replace NULL dates with a default date?
Use COALESCE around the extraction:
SELECT COALESCECASTorder_time AS DATE, ‘1900-01-01’ AS order_date FROM orders.

# 12. When should I convert dates to strings?
Only for display purposes in reports or UI. Keep the underlying data as a date type for calculations and filtering.

This guide is designed to help you reliably extract the date portion from any date/time value in SQL Server, with practical steps, real-world examples, and best practices you can apply immediately. If you want to dive deeper, you can check the included resources for official documentation and community insights.

Sources:

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