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Curated SQL Posts

So You Locked Out Your Sysadmin User…What Next?

Sreekanth Bandarla shows how you can recover from having your sysadmin user account locked out or removed:

In this blog post, let’s see how to regain admin access on a SQL Server Instance in case you lost it by mistake or for whatever reason. It’s not a very common scenario, but hey you never know. I ran into this some time last week(Fortunately it’s in our POC environment), Okay, Here’s the deal – we have a POC SQL Instance which was installed by an individual who is no longer working with us and apparently he forgot to make our DBA grp as sysadmins. Basically we don’t have admin rights to our own SQL Instance, SA account is disabled(Well, No one has no clue what that pwd was to begin with). So, how did we recover from this disastrous event?

This is the “fake rock with a key in it” workaround.  Also, a good reason why there should be as few local administrators on your Windows machines as you can get away with.

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Dataflows In Power BI

James Serra gives us a preview of Power BI Dataflows:

In short, Dataflows integrates data lake and ETL technology directly into Power BI, so anyone with Power Query skills (yes – Power Query is now part of Power BI service and not just Power BI Desktop and is called Power Query online) can create, customize and manage data within their Power BI experience (think of it as self-service data prep).  Dataflows include a standard schema, called the Common Data Model (CDM), that contains the most common business entities across the major functions such as marketing, sales, service, finance, along with connectors that ingest data from the most common sources into these schemas.  This greatly simplifies modeling and integration challenges (it prevents multiple metadata/definition on the same data).  You can also extend the CDM by creating custom entities.  Lastly – Microsoft and their partners will be shipping out-of-the-box applications that run on Power BI that populate data in the Common Data Model and deliver insights through Power BI.

A dataflow is not just the data itself, but also logic on how the data is manipulated.  Dataflows belong to the Data Warehouse/Mart/Lake family.  Its main job is to aggregate, cleanse, transform, integrate and harmonize data from a large and growing set of supported on-premises and cloud-based data sources including Dynamics 365, Salesforce, Azure SQL Database, Excel, SharePoint.  Dataflows hold a collection of data-lake stored entities (i.e. tables) which are stored in internal Power BI Common Data Model compliant folders in Azure Data Lake Storage Gen2.

Also check out the comments for some clarification on why you’d want to use Dataflows rather than doing the work directly in the data lake.

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SSIS TargetServerVersion Versus ProjectVersion

Andy Leonard explains the differences between the TargetServerVersion and ProjectVersion properties in SQL Server Integration Services:

Since I am still adjusting to the 9.5 hour time zone shift, I decided to poke around social media. My friend and brother from another mother, TJay Belt, had tagged me in a tweet. TJay was looking for answers about updating an SSIS 2014 project in SQL Server Data Tools (SSDT) for Visual Studio 2017.

TJay and I started this conversation a couple days ago when he mentioned a team member installed Visual Studio 2017 and experienced difficulties getting SSIS 2012 packages to execute in the debugger.

I don’t think I blogged about it, but I had some interesting experiences upgrading to Visual Studio 2017 and SQL Server Data Tools for VS 2017. The sum of my experience was: uninstall everything, then install Visual Studio, then install SSDT.

Read on for the answer.

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Power BI Administration With Powershell

Adam Saxton shares a video covering what is available in the MicrosoftPowerBIMgmt Powershell module:

The Power BI PowerShell and the Admin API allow you to quickly inventory your organization and manage workspaces and access. Forget the hastle of setting up the App registration within Azure Active Directory for API access, the Power BI PowerShell cmdlets take care of it for you. Just install and start using today!

Click through for that video.

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A Geometric Depiction Of Covariance

Nikolai Janakiev explains the concept of the covariance matrix using a bit of Python and some graphs:

In this article we saw the relationship of the covariance matrix with linear transformation which is an important building block for understanding and using PCASVD, the Bayes Classifier, the Mahalanobis distance and other topics in statistics and pattern recognition. I found the covariance matrix to be a helpful cornerstone in the understanding of the many concepts and methods in pattern recognition and statistics.

Many of the matrix identities can be found in The Matrix Cookbook. The relationship between SVD, PCA and the covariance matrix are elegantly shown in this question.

Understanding covariance is critical for a number of statistical techniques, and this is a good way of describing it.

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Calculating Cohort Lifetime Value With Excel And R

Eleni Markou shows how to calculate the lifetime value of a group of customers using two techniques:

A lot of ink has been spilled in developing various descriptions of the LTV, the majority of which ends up with mathematical formulas that are based on margin (m), retention rate (r) and discount rate (d) like the following (here):

However, this model appears to be not that realistic as it is based on a few quite restrictive assumptions:

  • Retention is assumed to be constant during the lifetime of a customer, i.e. the probability r of remaining retained remains the same across all months.
  • An infinite time horizon is assumed when calculating the present value of future cash flows.
  • The unit economics are supposed to be constant throughout lifetime which leads to a constant contribution margin.

Yet when dealing with an actual company, it easily becomes evident that none of the aforementioned conditions actually hold. Especially in early-stage businesses the size of the time periods across which you would like to calculate the LTV is month – or week – sized while at the same time the retention rate across them can vary significantly as the company’s products evolve quickly.

There’s a lot packed into that article, so give it a read.

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T-SQL Formatters

Kenneth Fisher links to a set of T-SQL formatters:

I have a hard time working with code that’s so badly formatted I can’t read it. Normally I’d just format it myself, but this was a good dozen pages long. So what did I do? I ran to twitter screaming for help.

And I got a lot of responses! Here were the recommendations followed by who recommended them:

My favorite is DevArt’s SQL Complete, which is a paid product, but covers almost perfectly our 30-some page T-SQL formatting guideline.

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Alerting On Missed Log Backups

Jamie Wick shows us how to build out an alert if we’ve exceeded a threshold for time since the last log backup:

The primary reason most transaction logs start to (unexpectedly) grow is that the transaction log hasn’t been backed up. This is usually caused by one of two situations: the log backup job failed, or the log backup job didn’t start. Most options for backing up SQL transaction logs (3rd party software, SQL Agent job, or maintenance plan) will include an alert/notification mechanism for when the job fails. Where some backup options are lacking is in notifying that a (log) backup that should have been taken, wasn’t. If the backup (or management) software doesn’t include an alert for missing backups, SQL Server (2008 & newer) has a solution. Policy Based Management (PBM) includes a policy (Last Log Backup Date) that will send an email notification when the last backup date/time exceeds a specified threshold.

A good use for a woefully underappreciated tool.

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SSMS: Analyze Actual Execution Plan

Grant Fritchey shows us something that the SSMS tools team snuck in on us:

One of the many new sets of functionality introduced in SQL Server Management Studio 17 is the new option “Analyze Actual Execution Plan.” If Microsoft continues down this path, there will be a lot of useful functionality at some point. If you haven’t yet looked at Analyze Actual Execution Plan, well, read on.

I hope they do expand this out.  I can see it being very beneficial, but it needs to look at a lot more than just cardinality estimations.

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Azure SQL Data Warehouse Restore Points

Arun Sirpal explains how backups work with Azure SQL Data Warehouse:

The question is how are backups done with Azure SQL DW?

It is very different from Azure SQL DB (which you would expect). Azure SQL DW has a totally different architecture to its classic database counter-part. Restore points are the key here. Automatic ones are taken throughout the day and are kept for seven days only. Worst case scenario is the time between the restore points will be eight hours hence giving an eight hour RPO (Recovery Point Objective).

You can also create manual restore points, as Arun shows.

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