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Database Weekly
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Editorial
 

Human frailty and the custodianship of data

I was sitting through a rather tedious meeting discussing the minutiae of data security when it occurred to me that IT was an easy target. When the GDPR panic swept through international corporate organisations, managers managed to calm themselves down with the comforting thought that this was purely an IT problem, and therefore a convenient stick with which to beat IT. Not so. When you look through the successful prosecutions that have happened since the GDPR passed into European law, you see that human stupidity and carelessness account for many of them, and organisational malice the bulk of the rest. The IT data breaches are spectacular in scale, and we are right to pore through the details and 'put our own house in order'. However, IT are, in general, the wrong target.

In terms of stupidity, we have as examples insurance companies accidentally distributing their entire client base along with eye-wateringly personal details, embedded unwittingly in a spreadsheet. We have embarrassing personal information in an email chain that eventually went outside the company. We have a social care organisation dumping old files, full of case notes, in a basement in an unsecured and unoccupied house. We have an employee of a care home loading an entire database of medical notes and personal information, taking it home, and then having the laptop stolen. Reading through accounts of successful prosecutions is fascinating.

There are so many ways of 'leaking' confidential data. I was reminded of the time I'd just visited the local amenity site for disposing of rubbish. As I dumped all my old monitors, I noticed a group of people disassembling all the dumped computers. Intrigued, I asked around, and discovered that they were given a guaranteed price for every hard drive. It was, surprisingly, well over the scrap price.

What I'm driving at is that the broader obligations that organisations have for the responsible curation of information can't be palmed off. It affects everyone in the organisation. When any sort of 'leakage' happens, you'll get a visit from the representative of your regulatory authority wearing a charcoal grey suit. The first thing he or she will first ask for is your DPIA, or Data Privacy Impact Assessment. All organizations that trade in Europe must formally assess the likelihood of data being 'leaked' or breached, and the impact it would have. This is a formal document that is signed off at board level. It doesn't matter where data may be concealed; like Schrödinger's cat, it is both breached and safe until you investigate and audit it. Where it is stored or hosted is irrelevant. You must prove that you are being responsible for good custody of it.

The board of directors, governors or trustees cannot claim they know nothing because it is now their legal obligation to know about it. If they haven't done it, and the data is breached even by human foolishness, this could lead, in Europe, to administrative fines of up to 2% of the organization's annual global turnover or €10 million, whichever is the greater.

Phil Factor

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The Weekly News
All the headlines and interesting SQL Server information that we've collected over the past week, and sometimes even a few repeats if we think they fit.
Vendors/3rd Party Products

Finding Correlated Rows Using EXISTS or COUNT

Should you always use EXISTS rather than COUNT when checking for the existence of any correlating rows that match your criteria? Does the former really offer "superior performance and readability". Louis Davidson investigates.

SQL Prompt 10: What’s New?

Tony Davis reviews the major new features of SQL Prompt 10, included improved 'ranking' of its code auto-completion suggestions, tab history improvements to make it easier to find 'lost' code, and auto-fixing of code that breaks code analysis rules.

How Fiducia & GAD scaled with SQL Monitor

When growth was expected on the horizon for Fiducia & GAD, hiring more DBAs was not an option. With SQL Monitor they were able to scale at an unprecedented rate- 150 new servers and 70+ applications in one year.

New release: SQL Prompt 10

n the latest version of SQL Prompt, we’ve made improvements to all the most popular features. Our new ranked suggestions algorithm prioritizes the suggestions most relevant to you, tab history improvements let you find old tabs easily and star favorites, and new auto-fixes help you resolve code issues quickly. With support for key features of SQL Server 2019, which was made available this week at Microsoft Ignite, SQL Prompt 10 gives you the latest tools to develop faster, improve code quality, and boost team productivity.

Administration

SQL Server 2019 Installation Enhancements for MAXDOP and Max Memory

Aaron Bertrand highlights some of the important changes coming in the installation process for SQL Server 2019, such as a new command-line argument, /SQLMAXDOP, allowing you to specify this value for automated installs.

Azure Synapse (SQL Data Warehouse and Data Lake)

Data Virtualization — The Evolution of the Data Lake

Data virtualization can be the solution to overcoming the shortcomings of a centralized repository.

Azure Synapse Analytics new features

James Serra summarizes new and forthcoming features for the enterprise data warehousing side of Azure Synapse Analytics (formally Azure SQL Data Warehouse).

Backup and Recovery

SQL Server Backup and Restore from URL

Many have covered how you should backup your SQL Server database to Azure storage (also known as backup to URL) but what about restoring?

Conferences, Classes, Events, and Webinars

SQLSaturday #916 - Bangladesh 2019

SQL Saturday comes to Bangladesh on Nov 16.

DMO/SMO/Powershell

Create a PowerShell Notebook for Azure Data Studio with PowerShell

The PowerShell to create a PowerShell Notebook, and to create a PowerShell Notebook that will create a PowerShell Notebook!

PowerShell: Puzzle Night At the User Group!

Solving numerical puzzles using PowerShell

Create SQL Server Database with PowerShell

Examining three different ways to create a database in PowerShell, using the Invoke-SqlCmd cmdlet, SMO, and dbatools.

Redgate Database Devops
Data Access / ORMs

Stop Mapping Stuff in Your Middleware: use SQL’s XML or JSON Operators Instead

If you’re writing a service that produces some JSON from your database model. What do you need? DTOs, factories, factory builders, Jackson, an XML and JSON mapper library? No, just some SQL.

Data Mining / Data Analysis

Naive Bayes Sentiment Analysis in Python After Preparing Data Using SQL

Sentiment analysis is a classification problem where data teams attempt to predict whether text is positive or negative in tone.

DevOps and Continuous Delivery (CI/CD)

Introduction to DevOps: 10 Guidelines for Implementing DevOps

Robert Sheldon discusses ten guidelines that will help organisations implement DevOps successfully.

ETL/SSIS/Azure Data Factory/Biml

Comparing Azure Data Factory Mapping Data Flows to SSIS

Mapping Data Flows is similar in look and feel to SQL Server Integration Services (SSIS). If you’re coming from an SSIS development background, Mapping Data Flows is a lot like the Data Flow tab. ADF Pipelines are a lot like the Control Flow tab.

SSIS Raw File Source and Destination Example

The Raw File source in SQL Server Integration Services (SSIS) can read data quicker than other file sources because it doesn't need to translate the data or parse the data when processing the file. This tip shows how to create Raw Files using SSIS that can also be used as source files, to take advantage of this storage format.

HA/DR/Always On/Clustering

Deploy a Big Data Cluster on AKS Using Azure Data Studio (Video)

Discussing the pros and cons of the different approaches, and explains the reasons why you might want to use AKS for your Big Data Cluster deployments.

Building a SQL Cluster Lab, Part 3: Availability Groups

How to create a multi-subnet Availability Group

Performance Tuning SQL Server

Miracle of OPTIMIZE_FOR_SEQUENTIAL_KEY

SQL Server 2019 provides another option to deal with the last-page insert contention – OPTIMIZE_FOR_SEQUENTIAL_KEY. It improves throughput for high-concurrency inserts into an ascending clustered index.

How to Think Like the SQL Server Engine: Included Columns Aren’t Free

If you want to make "lightweight" indexes, the big question isn’t, “Should this column be in the key or the includes?” It's “Should this column even be in the index at all?”

The Many Problems with SQL Server’s Index Recommendations

The index recommendations in the query plan and the ones in the DMVs both suffer from some pretty serious drawbacks. Brent Ozar lists them out.

Duplicate Indexes Explained

Possible duplicate indexes are those that very closely match Key/Included columns. Why do you care? Indexes have to be maintained.

PowerPivot/PowerQuery/PowerBI

What is Common Data Service and why it is important for you if you use Power Apps or Power BI?

What is the Common Data Service, what does it mean for you if you are a user of Power Apps or Power BI and how you can use it?

Next Level Power BI – M Language Basics

Paul Turley steps you through some essential mechanics of the the query script language of Power Query, known as “M” or the Microsoft Data Mashup language.

A low cost approach for paginated report subscriptions in Power BI

Paginated reports in Power BI offer a rich set of capabilities for printing, and the generation of report documents. Paginated reports can be exported to multiple document formats, and those exports can be scheduled and delivered via email. Unfortunately, for the moment at least, paginated reports require the use of a dedicated capacity, which can be cost prohibitive for some. This article describes a pattern that will help minimize the cost of using paginated reports for subscriptions.

Power BI Large Datasets: The Good, the Bad, and the Ugly

At Ignite 2019 Microsoft announced the public preview of large datasets in Power BI Premium, allowing the possibility of deploying organizational semantic models to Power BI. Having tested it with some large datasets, Teo Lachev shares some thoughts.

Power BI Filter Pane

Scott Murray explains the new Power BI Filter Pane and how to use it.

The importance of star schemas in Power BI

Creating a star schema in Power BI can improve performance and more importantly, ensure accurate results! This article shows why a star schema can fix some of the issues in your report.

Versioning and CI/CD for Power BI with Azure DevOps

Deploying Power BI content through a CI/CD pipeline makes it easy to move artifacts (pbix files) from one workspace to another, and even roll-back to an earlier version of the artifact if required, based on use of versioning in Git.

T-SQL

T-SQL Tuesday #120 What were you thinking?

A data intake process to leave you scratching your head.

Row numbers with nondeterministic order

There are times when you need to compute row numbers in no particular order; in other words, based on nondeterministic order. This could be across the entire query result, or within partitions. Examples include assigning unique values to result rows, deduplicating data, and returning any row per group.

The curious case of CHAR(0)

Strange behavior caused by a space at the start of a password.

Stack Overflow Demo Database Column Store Edition: Exploring Relationships

In part 4 of his series, Erik Darling gets you started exploring your new, venti-edition Stack Overflow column store database.

Capturing Insert and Update Counts from Merge

How to capture and store the number of records inserted, updated or deleted from a T-SQL Merge statement.

Stack Overflow Demo Database Column Store Edition Introduction

Erik Darling tackles a “Make Big” script to produce a large Stack Overflow database that is all clustered column store.

Query Store Options in SSMS 18.4

Erin Stellato explains some enhanced controls over Query Store behavior in SSMS 18.4

Testing Software

Principles of High-Value Software Testing

Tests help developers eliminate defects, build confidence, practice good design, and ideally all three. They also take time to write, run, and update–time that’s no longer available for other development tasks. High-value testing seeks to maximize the return on that investment.

Tools for Development

Docker, Git and dbatools

Grant Fritchey explains why database professionals can "no longer justify ignoring" these three tools: Docker, Git and DBATools

 
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