Achieve Data Consistency with Snowflake Convert Date to YYYY-MM-DD

Different systems and databases use various date formats. Converting date data into a consistent format will ensure accuracy across systems. For instance, you are collecting sales data from other regions that use different formats.

Combining and analyzing the sales data would be time-consuming and error-prone if the data is not standardized. By converting all the dates to a consistent format, such as YYYY-MM-DD, you can easily merge datasets, perform accurate time-based analysis, and generate consistent reports.

Snowflake is a tool for converting dates to a standardized format. It is a self-managed service that runs on cloud infrastructure. Snowflake architecture comprises three layers: storage, computing, and cloud services. Moreover, it offers functions, such as TO_CHAR and TO_VARCHAR, to convert a date data type into YYYY-MM-DD format.

Read along to learn more about the Snowflake convert date to YYYYMMDD format function.

Understanding Date Conversion in Snowflake

Date conversions in Snowflake are essential for several reasons. Converting date data type into a consistent format ensures dates and times are consistent, comparable, and usable within Snowflake. Using Snowflake for date conversions can enhance data quality, improve user experience, and ensure reliable analytics and reporting. 

Snowflake provides three primary data types for handling date, each used for different use cases:

1. DATE: This date type stores year, month, and day values.
2. TIMESTAMP: This date type includes the year, month, day, hour, minute, second, and milliseconds ( up to 6 decimals).
3. TIMESTAMP_LTZ, TIMESTAMP_NTZ, TIMESTAMP_TZ: These date types are similar to TIMESTAMP but include time zone information.

• TIMESTAMP_LTZ: It stores the timestamp with the local time zone.
• TIMESTAMP_NTZ: It stores the timestamp without any time zone.
• TIMESTAMP_TZ: It stores the timestamp along with the UTC time zone.

These data types allow for comprehensive storage and manipulation of date information in Snowflake. Here is a list of conversion functions that can guide you in the conversion process. Let’s discuss two of the functions in detail:

• TO_DATE function in Snowflake converts an input expression, typically a string, into a date. It is useful when you need to parse strings in various formats into a date type. In the case of a JSON input variant, the output is NULL.
  • Syntax: 

TO_DATE( <string_expr> [, <format> ] ) 

• Examples of Snowflake convert date in YYYYMMDD format to date using the TO_DATE function:
• Converting to a default format YYYY-MM-DD:

SELECT TO_DATE('2024-05-10');

• Converting to DD-MM-YYYY format:

SELECT TO_DATE('2024-05-10', ‘DD-MM-YYYY’); 

• Convert to MM/DD/YYYY format:

SELECT TO_DATE('2024-05-10', ‘MM/DD/YYYY’)

• The DATE function is a shorthand for directly converting string literals to a date type. It assumes the input follows the strict date format YYYY-MM-DD, making it less flexible for varied input formats.

Syntax: 

DATE( <string_expr> [, <format> ] )

Example:

SELECT DATE ('2024-05-10');

How to Convert the Date Format of a Column From YYYY-MM-DD to DD/MM/YYYY 

Due to hardcoded constraints or compatibility issues, some legacy systems or older applications might require dates to be in the DD/MM/YYYY format. To convert the date format from YYYY_MM_DD to DD/MM/YYYY in Snowflake, you can use the TO_VARCHAR function. This function formats the date as a string in the desired format. 

• Convert the current system date to DD/MM/YYYY format: 

SELECT TO_VARCHAR(CURRENT_DATE(), ‘DD/MM/YYYY’);

• You can also convert a string to a date format. First, convert the string to date format using the TO_DATE function, then use the TO_VARCHAR function to change the date format accordingly:

SELECT TO_VARCHAR(TO_DATE(‘1991-09-08’, ‘YYYY-MM-DD’), ‘DD/MM/YYYY’);

How to Get the Output in YYYYMMDD, YYYYMM, YYYY Format Using the Current_Date() or Current_Timesatmp() Function

You can convert date to YYYYMMDD in Snowflake and also into different formats like YYYYMM or YYYY using the TO_CHAR function. This function converts dates and timestamps to strings in the specified format.

1. Current_Date()

To get current dates in YYYYMMDD, YYYYMM, and YYYY formats, use the following SQL statements:

SELECT TO_CHAR(CURRENT_DATE(), 'YYYYMMDD') AS current_date_YYYYMMDD;

SELECT TO_CHAR(CURRENT_DATE(), 'YYYYMM') AS current_date_yyyymm;

SELECT TO_CHAR(CURRENT_DATE(), 'YYYY') AS current_date_yyyy;

Output:

The result will be formatted strings representing the current date in the specified Snowflake convert date to YYYYMMDD, YYYYMM, and YYYY formats.

current_date_YYYYMMDD	current_date_yyyymm	current_date_yyyy
20240531	202405	2024

2. Current_Timestamp()

To get the current timestamp in YYYYMMDD, YYYYMM, and YYYY formats, use the following SQL statements:

SELECT TO_CHAR(CURRENT_TIMESTAMP(), 'YYYYMMDD') AS current_timestamp_YYYYMMDD;

SELECT TO_CHAR(CURRENT_TIMESTAMP(), 'YYYYMM') AS current_timestamp_yyyymm;

SELECT TO_CHAR(CURRENT_TIMESTAMP(), 'YYYY') AS current_timestamp_yyyy;

Output:

The result will be formatted strings representing the current timestamp in the specified Snowflake convert date to YYYYMMDD, YYYYMM, and YYYY formats.

current_timestamp_YYYYMMDD	current_timestamp_yyyymm	current_timestamp_yyyy
20240531	202405	2024

The TO_CHAR function in Snowflake change date format can convert dates into YYYYMM format without needing CURRENT_DATE() and CURRENT_TIMESTAMP() functions. For example, if you have a date column in a table and want to convert the values in that column to the YYYYMM format, you can use the TO_CHAR function in a SELECT statement.

Syntax:

SELECT TO_CHAR(order_date, 'YYYYMM') AS updated_order_date
FROM orders;

Example:

SELECT TO_CHAR(TO_DATE('2024-05-30', 'YYYY-MM-DD'), 'YYYYMM') AS updated_date;

This above query converts the date in Snowflake to YYYYMM. The string ‘2024-05-30’ is formatted into YYYYMM, resulting in ‘202405’.

Error Handling Conversion Functions 

Handling errors during conversion in Snowflake is crucial to ensuring data integrity and preventing disruptions in data processing. Snowflake provides several functions and techniques to carefully handle mistakes and manage invalid date formats.

The error-handling conversion functions have a TRY_ prefix, which returns a NULL value instead of raising an error. Here are some functions and examples for error-handling date conversions.

1. TRY_CAST

This function converts a value of one data type to another.

Syntax: 

TRY_CAST( <source_string_expr> AS <target_data_type> )

Example:

SELECT TRY_CAST(’05-Mar-2023′ AS TIMESTAMP);

+————————————–+

| TRY_CAST(’05-MAR-2023′ AS TIMESTAMP) |

|————————————–|

| 2016-03-05 00:00:00.000     |

+————————————–+

2. TRY_TO_BINARY

This function converts an input value expression to binary.

Syntax: 

TRY_TO_BINARY( <string_expr> [, '<format>'] )

Example:

• Step 1: Initially, create a table and insert values.

CREATE TABLE strings (v VARCHAR, hex_encoded_string VARCHAR, b BINARY);

INSERT INTO strings (v) VALUES

    ('01'),

    ('A B'),

    ('Hello'),

    (NULL);

UPDATE strings SET hex_encoded_string = HEX_ENCODE(v);

UPDATE strings SET b = TRY_TO_BINARY(hex_encoded_string, 'HEX');

• Step 2: Call TRY_TO_BINARY()

SELECT v, hex_encoded_string, TO_VARCHAR(b, ‘UTF-8’)

  FROM strings

  ORDER BY v

  ;

+——-+——————–+————————-+

| V     | HEX_ENCODED_STRING | TO_VARCHAR(B, ‘UTF-8’)  |

|——-+——————–+————————+

| 01    | 3031                  | 01                      |

| A B   | 412042             | A B                    |

| Hello | 48656C6C6F   | Hello                  |

| NULL  | NULL             | NULL                 |

+—–+———-+————+

3. TRY_TO_BOOLEAN

This function converts an input expression to a boolean value.

Syntax: 

TRY_TO_BOOLEAN( <string_expr> )

Example:

SELECT TRY_TO_BOOLEAN(‘True’)  AS “T”, 

       TRY_TO_BOOLEAN(‘False’) AS “F”,

       TRY_TO_BOOLEAN(‘Oops’)  AS “N”;

+——+——-+———+

| T      | F      | N         |

|——-+——-+———-|

| True | False | NULL |

+——+——–+———+

4. TRY_TO_DATE

This function converts an input expression to a date.

Syntax: 

TRY_TO_DATE( <string_expr> [, <format> ] )

 TRY_TO_DATE( '<integer>' )

Example:

SELECT 

  TRY_TO_DATE(‘2024-05-10’) AS valid_date, 

  TRY_TO_DATE(‘Invalid’) AS invalid_date;

+——————+———————+

| VALID_DATE | INVALID_DATE |

|——————-+———————-|

| 2024-05-10    | NULL                 |

+——————+———————-+

5. TRY_TO_TIME

This function converts an input expression into time.

Syntax:

TRY_TO_TIME( <string_expr> [, <format> ] )

TRY_TO_TIME( '<integer>' )

Example

SELECT TRY_TO_TIME(’12:30:00′), TRY_TO_TIME(‘Invalid’);

+———————————–+————————————+

| TRY_TO_TIME(’12:30:00′) | TRY_TO_TIME(‘INVALID’) |

|————————————-+————————————|

| 12:30:00                              | NULL                                  |

+——————-+———————+

6. TRY_TO_TIMESTAMP/ TO_TIMESTAMP_*

This function converts an input expression into a timestamp.

Syntax:

timestampFunction ( <string_expr> [, <format> ] )

timestampFunction ( '<integer>' )

Where:

timestampFunction ::=

    TRY_TO_TIMESTAMP | TRY_TO_TIMESTAMP_LTZ | TRY_TO_TIMESTAMP_NTZ | TRY_TO_TIMESTAMP_TZ

Example

SELECT TRY_TO_TIMESTAMP(‘2024-01-15 12:30:00’), TRY_TO_TIMESTAMP(‘Invalid’);

+————————————————————+———————————————+

TRY_TO_TIMESTAMP(‘2024-01-15 12:30:00’)| TRY_TO_TIMESTAMP(‘INVALID’) 

|————————————————————-+———————————————-|

2024-01-15 12:30:00.000                                  | NULL                                              |

+————————————————————+———————————————-+

Use Hevo to Deploy the Date Conversion Functions in Snowflake

Snowflake convert date to YYYYMMDD may face challenges related to date conversions in different time zones during data processing. Hevo allows you to transform manipulate and format your date data as required before it gets loaded into Snowflake, ensuring data integrity and consistency.

Hevo is an ELT no-code data pipeline platform that cost-effectively automates flexible data pipelines to your needs. With more than 150+ prebuilt connectors, you can integrate your data, clean, and transform to make it analysis-ready. Once the Snowflake connection is set with Hevo, you can easily extract data without writing code.

Benefits of Using Hevo

• Data Transformation: Hevo offers a built-in transformation capability that allows you to clean and prepare your date data type before loading it into Snowflake. Hevo ensures the date is in the correct format and standardizes the date format across different sources to ‘YYYY-MM-DD’, which Snowflake can easily interpret.
  
• Automated Schema Mapping: Hevo automatically detects the schema of the source data, including date data types, and maps it to the appropriate data types in the Snowflake schema. It lets you choose between Full and incremental Mappings according to your data replication requirements.
  
• Incremental Data Loading: Hevo’s incremental data loading allows you to efficiently ingest and synchronize only the changed or new data from your source systems into Snowflake. For date data type conversions, it ensures that only the relevant date changes are processed, minimizing the load on your Snowflake environment. 

Conclusion 

Snowflake provides robust date conversion functions widely used for handling date and time data. However, some disadvantages to using these functions, such as writing custom syntax using TO_CHAR and TO_DATE, can be error-prone and lead to potential bugs in date conversion logic. Also, date conversion functions are sensitive to regional settings. 

Want to take Hevo for a spin? for a 14-day free trial and simplify your data integration process.

However, you can overcome these disadvantages with Hevo. This cloud-based data integration platform can significantly streamline your date conversion process before loading into Snowflake. Hevo lets you simplify the date formats from various sources into a desired format before loading it in Snowflake. 

FAQs

1. How do you convert the date format in Snowflake?

You can convert a string type to a date type and later change its format using the TO_VARCHAR function. The following SQL command shows how to convert Snowflake date format mm/dd/yyyy:

SELECT TO_VARCHAR(TO_DATE(‘08/09/2022’, ‘DD/MM/YYYY’), ‘MM-DD-YYYY’);

2. How to change the date format in Snowflake?

You can convert a date to the U.S. format MM/DD/YYYY using CURRENT_DATE and TO_VARCHAR functions.

SELECT TO_VARCHAR(CURRENT_DATE(), ‘MM/DD/YYYY’);

3. How to use DATEDIFF in Snowflake?

DATEDIFF Snowflake function is used to perform efficient data analysis involving date, time, or timestamp expression.

The Syntax is as follows,

DATEDIFF ( <Date_or_Time_Part>, <Start_Date_or_Time_Expression1>, <End_Date_or_Time_Expression2> )

Example:

SELECT DATEDIFF(month,'2023-11-02', '2024-03-20');

This SQL query calculates the months between 2023-11-02 and 2024-03-20 using DATEDIFF(). The result is three months.