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Day: January 28, 2016

What Is Power BI?

Published 2016-01-28 by Kevin Feasel

Angela Henry gives a high-level overview of Power BI:

There are lots of reasons to use Power BI, other than, it’s so cool.  For instance, Power BI makes it easy to see, in one glance, all the information needed to make decisions.  It also allows you to monitor the most important information about your business.  Power BI makes collaboration easy and when I say easy I mean EZ!  You can also create customized Dashboards tailored to those C-Suite folks or make a completely different dashboard based on the same data for those that actually do the work.

I’m personally astounded at how far visualization tools have come in half a decade.

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Spatial Data

Published 2016-01-28 by Kevin Feasel

Dave Mattingly has a multi-part series on spatial data.  This is part 5 (with links to the previous).

 

If you’re interested in spatial data, this looks like a fantastic set of blog posts which mesh well with Dave’s presentation on spatial data.

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Migrating To Azure SQL Database

Published 2016-01-28 by Kevin Feasel

James Serra has a good post on moving your on-premise SQL Server instance up to Azure SQL Database:

In this migration process you migrate both your schema and your data from the SQL Server database in your current environment into SQL Database, provided the existing database passes compatibility tests.  Fortunately with SQL Database Version 12 (V12), there are very few remaining compatibility issues other than server-level and cross-database operations (see Azure SQL Database Transact-SQL differences).  Databases and applications that rely on partially or unsupported functions will need some re-engineering to fix these incompatibilities before the SQL Server database can be migrated.

Two years ago, I would have laughed at the idea.  Right now, I’m skeptical.  My expectation is that, two years from now, this will be my default answer for non-sensitive data.

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Defaults Not Guaranteed Equal

Published 2016-01-28 by Kevin Feasel

Michael J. Swart shows that two DATETIME2 columns with default constraints will not necessarily show the same value upon insertion:

If I want to depend on these values being exactly the same, I can’t count on the default values.

Default constraints will fill in the correct value, but as Michael notes, “the correct value” is calculated each time.  Also, note that his results are about a millisecond off, so if you’re just using DATETIME, the frequency of observation of this occurrence will be lower, as DATETIME is only good to 3 milliseconds.  That’s not a good reason to use DATETIME, though.

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