Data Quality and Data Profiling
David Loshin describes the benefits of the combination of the bottom-up aspects of data profiling with a top-down analysis phase for establishing criteria for data quality management.
2009-01-01
2,313 reads
David Loshin describes the benefits of the combination of the bottom-up aspects of data profiling with a top-down analysis phase for establishing criteria for data quality management.
2009-01-01
2,313 reads
In the first of a series of articles on the tricks of tackling temporal data in SQL, Joe Celko discusses SQL's temporal data types and agonizes over the fact that, although there are ANSI/ISO Standards for temporal operations in SQL, every vendor has something different.
2008-12-31
1,141 reads
In a previous tip on Disaster Recovery Procedures in SQL Server 2005 Part 1, we have seen how we can come up with a disaster recovery procedure in SQL Server 2005. There are other ways to increase availability of your highly critical database in SQL Server 2005. What are those other options?
2008-12-31
2,725 reads
Today many companies determine to publish their data on the Internet trying to expand their business and make their information more accessible. The IT industry proposes a wide range of original solutions for resolving data inconsistency problems that publishers inescapably face when exporting their data as they need to properly access, process and interchange large amounts of information mainly through the web.
2008-12-30
2,236 reads
Yan Pan explains how to set up proxies in SQL Server 2000, 2005 and 2008, and compares the differences between them
2008-12-30
4,305 reads
At first glance, a client appeared to be violating a cardinal rule of data warehousing. However, Bill Inmon's further investigation revealed that perhaps their actions were acceptable.
2008-12-29
2,789 reads
OPENROWSET is a T-SQL function that allows for reading data from many sources including using the SQL Server’s BULK import capability.
2008-12-29
6,687 reads
When creating tables it is difficult to determine exactly how the data will be accessed. Therefore when clustered indexes are chosen they are often just the ID column that makes the row unique. This may be a good choice, but once the application has been used and data access statistics are available you may need to go back and make some adjustments to your tables to ensure your clustered indexes are providing a benefit and not a drain on your applications.
2008-12-26
3,880 reads
This article describes the new Peer-to-Peer replication features in SQL Server 2008
2008-12-26
2,534 reads
We use the FTP task in SSIS to process a number of files from an FTP server. We would like to implement a step in our SSIS packages that would retrieve the list of files that are available on the FTP server before we try to process them.
2008-12-24
4,073 reads
By HeyMo0sh
Over time, I’ve realised that one of the hardest parts of cloud management isn’t...
By HeyMo0sh
One of the biggest challenges I’ve faced in cloud operations is maintaining clear visibility...
By Steve Jones
I come to Heathrow often. Today is likely somewhere close to 60 trips to...
Comments posted to this topic are about the item Fun with JSON II
Comments posted to this topic are about the item Changing Data Types
Comments posted to this topic are about the item Answering Questions On Dropped Columns
I have some data in a table:
CREATE TABLE #test_data
(
id INT PRIMARY KEY,
name VARCHAR(100),
birth_date DATE
);
-- Step 2: Insert rows
INSERT INTO #test_data
VALUES
(1, 'Olivia', '2025-01-05'),
(2, 'Emma', '2025-03-02'),
(3, 'Liam', '2025-11-15'),
(4, 'Noah', '2025-12-22');
If I run this query, how many rows are returned?
SELECT t1.[key] AS row,
t2.*
FROM OPENJSON(
(
SELECT t.* FROM #test_data AS t FOR JSON PATH
)
) t1
CROSS APPLY OPENJSON(t1.value) t2; See possible answers