Enhance Data Integrity With Snowflake Date Format

Data and time information are essential for accurately capturing, organizing, and processing data for effective data management. These functions help you extract information from the storage system in a logical manner so that you can analyze the data to make informed business decisions.

You must understand how date/time functions work to implement them appropriately. The date format in Snowflake tells you how the date/time functions are structured and presented in a Snowflake Data Cloud. Utilizing these date/time functions will help you make precise calculations related to your business data. 

This article will explain the Snowflake date format, how to manage and change date formats, some practical use cases, and more.

What is Snowflake Date Format?

The Snowflake cloud platform supports various types of data/time functions. These date format Snowflake functions represent how your date-based data is structured and stored in the platform.

Date formatting helps you manage different data types and formats related to date/time parts and helps you extract the information you need. The Snowflake date formats support a wide range of analytics operations. You can perform operations such as formatting date and time from numerical to string value, adding extra date parts, applying mathematics calculations, and more. 

For example, if you want to convert a date column from string to date format, you can use the TO_DATE function. Or, if you want to extract a part of a current date or a specific date, then you can use the DATE_PART function. 

Managing Date and Time Data Types Using Date Format in Snowflake 

The Snowflake date format specifies various data types and formats that Snowflake supports. Here are some components of data format functions that help you enhance your operational efficiency.

Key Components of Snowflake Date Format

1. DATE

Snowflake supports DATE data types, which accept dates in the following format: 

• The Standard Date Format: YYYY-MM-DD , eg., 2024-05-24
• US Date Format: MM-DD-YYYY, eg., 05-24-2024
• European Date Format: DD-MM-YYYY, eg., 24-05-2024

2. TIME

The format date Snowflake supports a single TIME data type, which stores the value of the time part in the following form: 

HH:MI:SS, eg., 22:45:19

The time value is in 24-hour format, where the values must be between <00:00:00> and <23:59:59.999999999>

3. TIMESTAMP

The TIMESTAMP in Snowflake is user-specified. It is associated with one of the TIMESTAMP_* variations and is automatically used in database operations.

4. Calendar

Snowflake supports the Gregorian Calendar for all dates and timestamp formats. The Gregorian Calendar started in 1582, so it does not recognize dates before that. 

5. Date and Time Constants 

The constants are the fixed date/time values. The values are enclosed in single quotes. 

6. Interval Constants

You can use the interval constant to add or subtract a date, time, or timestamp period.

How does Snowflake Determine Which Input/Output Format to Use

Snowflake determines the input and output format of date/time functions in two ways: 

• Session Parameters
• File Format Options for Loading and Unloading the Date Format

Let’s see how these methods work. 

Session Parameters

A session parameter determines how date-based data is passed in or out of Snowflake. It also tells you which time zones are used in time and timestamp formats. These parameters can be set on an account, user, or session level. You can use the SHOW PARAMETERS command to see what parameters are set on the current sessions.

• INPUT FORMATS

Three parameters define the date, time, and timestamp formats recognized for DML (data manipulation language). 

• DATE_INPUT_FORMAT
• TIME_INPUT_FORMAT
• TIMESTAMP_INPUT_FORMAT

These parameters include operations such as COPY, INSERT, and MERGE. The default value for three of them is AUTO. Snowflake format date functions try to match the string value for date, time, and timestamp with the input expression.

The values with which the date/time input is matched are specified in the Snowflake format list: Supported Formats for AUTO Detection. If the format matches, Snowflake accepts the string. If it does not match the value, it will return an error.

• OUTPUT FORMATS

The following parameters define the date, time, and timestamp format for output from Snowflake: 

• DATE_OUTPUT_FORMAT
• TIME_OUTPUT_FORMAT
• TIMESTAMP_OUTPUT_FORMAT
• TIMESTAMP_LTZ_OUTPUT_FORMAT
• TIMESTAMP_NTZ_OUTPUT_FORMAT
• TIMESTAMP_TZ_OUTPUT_FORMAT
• TIMESTAMP_TYPE_MAPPING
• TIMEZONE

File Format Options for Loading and Unloading the Date/Time Values

Snowflake provides format options for loading and unloading the data from Snowflake tables. 

• DATA_FORMAT
• TIME_FORMAT
• TIMESTAMP_FORMAT

You can specify these options directly in a COPY command or in a named stage or file format object, which is referenced in a COPY command.

• DATA LOADING

When performing data loading, the above options help you format date, time, and timestamp values. They override the parameter settings in session parameters. The default for the format options in data loading is AUTO, where COPY INTO <table> tries to match the string values to the formats listed in the supported format list. 

• DATA UNLOADING 

When you perform data unloading in Snowflake, you can use the following option to specify the date/time-based formats in a specified stage. These options have a default AUTO setting. 

• DATE_OUTPUT_FORMAT
• TIME_OUTPUT_FORMAT
• TIMESTAMP_*_OUTPUT_FORMAT

Practical Uses of Snowflake Date Format 

Here are some use cases for Snowflake date format conversion using formatting.

How to Convert a Date/Time Value to a String

You can use the TO_CHAR function to convert a date/time value into a string. By converting the timestamp value, you can obtain better insights into the data related to a particular domain for a specific time. This allows you to implement strategies for better outcomes. For instance, you can analyze customer data to determine the peak shopping hours and run ads at that time to increase the conversion rate.

SELECT TO_CHAR (CURRENT_TIMESTAMP, ‘YYYY-MM-DD HH:MI:SS’); 

The output of the following command will be 2024-05-27 12:50:56.

How to Filter Data Between Specific Date Ranges

By filtering data between specific dates, you can evaluate your business processes, identify areas of improvement, and allocate resources efficiently. 

Suppose you have to retrieve records from the order table for the last 30 days. You can use the following command:

SELECT order_id, order_date, order_amount

FROM order where order_date BETWEEN DATEADD(day, -30, CURRENT_DATE) AND CURRENT_DATE;

In the above command, The DATEADD function helps you to specify the timeline of the last 30 days. The result will be in the following format.

order_id	order_date	order_amount
101	2024-04-28	300
102	2024-05-11	250
103	2024-05-24	140

The above output tells you how much a customer is willing to spend on a particular product. It lets you evaluate the product and modify your pricing policy accordingly.

How to Insert a Specific Date in a Column Inside a Table 

Inserting a specific date into a column helps you systematically organize and validate data and track events over time. For instance, you want to record delivery dates for each month’s shipment to keep track of delays.

In the example below, you can use the ‘DATE’ keyword to insert a specific date value in table t1 inside column d1. 

CREATE TABLE t1 (d1 DATE);

INSERT INTO t1 (d1) VALUES (DATE '2011-10-29');

To check the value of the output, you can use the command:

SELECT* FROM  t1; 

How to Change Date Format in Snowflake

You can change a date value in Snowflake by changing the date format. This provides uniformity across your organization, making it easier to generate accurate reports and maintain consistency.

Use the following command to format the current date: 

SELECT TO_CHAR(CURRENT_DATE, ‘MM-DD-YYYY’) as formatted_date; 

The result of the following query will be 05-24-2024.

Considerations To Format Date in Snowflake

• When working with an integer data entity, you must directly enter the values as numbers instead of using quotes. This helps you maintain data consistency and integrity.
• Interval constants are not data types; they are functions that can be used only for performing arithmetic operations on date/time values. You also need to be careful when specifying the order in which the increment is calculated while dealing with leap year.
• The time and timestamp values do not support simple arithmetic calculations.

It is essential to consider the vulnerabilities of the date/time functions in Snowflake while performing queries. This can help you avoid discrepancies and maintain data consistency within your working time zone session. You can standardize the globally collected data using ELT tools such as Hevo, which can help maintain data consistency while performing date/time operations.

Benefits of Format Date Snowflake Functions

• Enhance Data Interpretation: The Snowflake date format improves the readability of date/time functions, making it easier for analysts and stakeholders to interpret information. 
• Improve Data Compatibility: The date format in Snowflake lets you customize the date/time formats according to your requirements, improving its compatibility while integrating with other systems. 
• Easy Analysis: Formatting your date/time values can give you a more accurate view of your data, making it easy to sort, retrieve, and filter. 

Simplify Snowflake ELT and Integration Using Hevo 

Hevo is a real-time ELT platform that streamlines your source data into Snowflake, reflecting the latest changes through its no-code, flexible, and automated data pipeline. It helps you standardize the timezone during data processing and loading. You can overcome the vulnerability associated with the date/time by harmonizing the values across the database. 

Hevo provides a Timeutils class that allows you to set methods for working with time/date values. This means you can perform transformations on your source data and test your script on a sample event before you deploy it to the destination. It includes formatting time values, converting to the required date format, or performing calculations. Besides these, Hevo offers many built-in features that help you transform your data, making it analysis-ready. Let’s look at some of them.

• Automated Schema Mapping: The automated schema mapping feature automatically reads and maps your source data schema to your destination. You don’t manually have to check every date/time value data field, as the feature helps you map and load them accurately in Snowflake.
• Data Transformation: Hevo provides two types of transformations: Python-based and drag-drop. They allow you to set a standard time zone while data processing, ensuring your data is consistent and aligned.
• Incremental Data Loading: Incremental data loading lets you capture the changes in the source data and load only them, not the whole data set. It ensures data integrity when dealing with data/time values.
• Historical Data Sync: This feature of Hevo allows you to go back in time by syncing historical data from source to destination. It helps you to compare data from different time periods. 
• Object-Level Control: The object-level control feature allows you to perform selective data ingestion. This is beneficial when filtering the records based on the current date.

Learn More About:

• Mastering DATE_PART Snowflake for Powerful Date Operations
• Understanding the TO_DATE Function in Snowflake

Conclusion

Snowflake data format improves data compatibility by formatting date/time values according to specific requirements. These functions enhance data analysis and help you prepare accurate reports for informed decisions. To ensure data consistency across various systems and maintain high data quality, you can use ELT tools such as Hevo. Its robust data integration capabilities seamlessly combine with Snowlake’s features, enhancing data management by standardizing the data format across the organization.

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