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Why Would I Ever Need to Partition My Big ‘Raw’ Data?

Whether you are running an RDBMS, or a Big Data system, it is important to consider your data-partitioning strategy. As the volume of data grows, so it becomes increasingly important to match the way you partition your data to the way it is queried, to allow 'pruning' optimisation. When you have huge imports of data to consider, it can get complicated. Bartosz explains how to get things right; not perfect but wisely.

2016-11-22

3,345 reads

External Article

How to Start Big Data with Apache Spark

It is worth getting familiar with Apache Spark because it a fast and general engine for large-scale data processing and you can use you existing SQL skills to get going with analysis of the type and volume of semi-structured data that would be awkward for a relational database. With an IDE such as Databricks you can very quickly get hands-on experience with an interesting technology.

2016-11-18

3,131 reads

External Article

More Power BI to your Elbow

Power BI Desktop continues to evolve. There have been many improvements to the reporting side that together make it easier to get from the data to the visualisation as quickly as possible. You can now create line charts that let users drill down into hierarchical data. There are now ways of adding dynamic reference lines to a visualization that provide users with relevant reference points. Robert Sheldon demonstrates how to combine these features to great effect.

2016-11-16

3,166 reads

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Question of the Day

Multiple Values Inserted

I have this code on SQL Server 2022. What happens when it runs all at once? 

DROP TABLE IF EXISTS dbo.Commission
GO
CREATE TABLE dbo.Commission
(id INT NOT NULL IDENTITY(1,1) CONSTRAINT CommissionPK PRIMARY KEY
, salesperson VARCHAR(20)
, commission VARCHAR(20)
)
GO
INSERT dbo.Commission
( salesperson, commission)
VALUES
( 'Brian', 12 ),
( 'Brian', 'None' )
GO
 

See possible answers