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How to Avoid Gaps in Data in Snowflake

While storing the data, we may get some gaps in data. But, we should not have the gaps in the report data. So, by using Common Table Expressions(CTE), we create the series of time/date values that do not have any gaps. We will study to create a time/date values series in this blog.

Snowflake - Avoid the Gaps in Data

In Snowflake, we must group the data by time. However, we don’t require the gaps in our report data. We should create the series of time/date values that do not have gaps through the common table expression:

set start_date = ‘2022-06-02’
set end_date = ‘2022-06-30’

with cte_data (data_rec) as (

select to_date($start_date)
union all
select to_date(dateadd(day, 1, date_rec))
from cte_date1
where date_rec <  $end_date
)
select date_rec1
from cte_date1

date_rec1

2022-06-02
2022-06-03
2022-06-04
2022-06-05
2022-06-06
….
2022-06-30

We left to join our data series against the gapless series. Creating the count of the sessions for every day:

set start_date = ‘2022-06-02’
set end_date = ‘2022-06-30’
with cte_date (date_rec) as (
select to_date($start_date)
union all
select to_date(dateadd(day, 1, date_rec))
from cte_date1
where date_rec < $end_date
)

select
cte_date.date_rec,
count(s.id) as session_ct
from cte_date
left outer join sessions s on to_date(s. start_date) = cte_date.date_rec
group by date_rec;

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Conclusion

By creating a series of time or date values through common table expressions, we can avoid gaps in data. I hope this blog offers sufficient information about avoiding gaps.

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If you have any queries, let us know by commenting below. 

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Last updated: 04 Apr 2023
About Author

Kalla Saikumar is a technology expert and is currently working as a Marketing Analyst at MindMajix. Write articles on multiple platforms such as Tableau, PowerBi, Business Analysis, SQL Server, MySQL, Oracle, and other courses. And you can join him on LinkedIn and Twitter.

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