Tag: cloud_storage
Handling null values in Google Bigquery: Best practices for data cleaning
1. Overview of NULL in Databases In the realm of databases, the term “NULL” represents the absence of any specific…
Navigating date arithmetic in Google BigQuery : Subtracting days from a date column
In data analysis, sometimes you may need to perform arithmetic on date columns, such as subtracting a number of days…
Google BigQuery: Converting Timezones in a datetime column – Sample code inside
Mastering timezone conversion in Google BigQuery In the world of global data analytics, dealing with data across multiple time zones…
Extracting minutes from timestamp in Google BigQuery and handling in PySpark
Often in data analytics, there’s a need to extract specific parts of a date or timestamp for more granular analysis….
Google BigQuery: Truncate date and timestamp – Example with sample data included
When dealing with data in Google BigQuery, especially time-series data, it’s common to want to truncate dates and timestamps to…
Comparing two tables in Snowflake – An easy to implement document
When working with Snowflake, there might be scenarios where you need to compare two tables to determine differences. These differences…
Google BigQuery: Filling null dates with previous row value
In the data world, it’s not uncommon to encounter scenarios where certain records might have missing date values. In BigQuery,…
Translating timezone handling from Redshift to Snowflake
When migrating or synchronizing data workflows between different cloud data platforms, subtle differences in SQL function implementations can become a…
Step-by-step guide on executing PySpark code from Snowflake Snowpark to read a DataFrame:
Here are the steps on how to execute PySpark code from Snowflake Snowpark to read a DataFrame: 1. Open Snowsight…
Snowflake : Identifying Non-Matching Timestamps and Customer IDs between Two Tables in Snowflake: An SQL Approach
SQL Method: Find Unmatched Timestamps/IDs If you want to find the records where both the ts (timestamp) and customerid columns…
