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Month: September 2021

The Reason for Tail Log Backups

Chad Callihan explains why we need tail log backups:

When you are migrating a database from one server to another, how can you be sure to backup all transactions? Sure, you can notify the client and let them know “there will be a short outage at 8AM so please stay out of the application at that time.” Can you really trust that? Of course not. Let’s demonstrate the steps needed to include all transactions with the tail-log backup.

Protip: if you build your application such that nobody wants to use it, you can migrate the database much more easily. Assuming you don’t want to follow that outstanding advice, Chad has you covered.

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Software Development Estimation is Hard

Andy Leonard makes a point:

I recently blogged about punching developers in the brain when a software deliverable deadline is slipping. The title of the post is The Question Unasked. In this post, I would like to address software development estimation.

In the past, I have stated “Either all software developers are pathological liars or software development is inherently inestimable.”

Read on for Andy’s take. For mine, the overly short version is that incentives are set up for software estimation to fail due to perverse incentives and a lack of requirements. Ask the question, “How long will it take to build a skyscraper?” and you might get some answer, but it certainly won’t be the answer to the pertinent question, “How long will it take to build this skyscraper?” That’s because we haven’t talked at all about location, building plans, blueprints, regulatory requirements, financing, or any of the hundreds of other things which organizations talk about and do before they start slapping mortar on bricks. With software development, we’re expected to wing it and solve all of those sorts of problems along the way. Making it even better, more often than not, the skyscraper “pivots” to being a suspension bridge.

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Where Kafka Connect Fits

Shivani Sarthi explains the value of Kafka Connect:

Kafka connect is not just a free, open source component of Apache Kafka. But it also works as a centralised data hub for simple data integration between databases, key-value stores etc. The fundamental components include-

– Connectors

– Tasks

– Workers

– Converters

– Transforms

– Dead letter Queue

Moreover it is a framework to stream data in and out of Apache Kafka. In addition, the confluent platform comes with many built-in connectors,used for streaming data to and from different data sources.

Click through for information on each component.

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Analog and Digital Clocks in R

Tomaz Kastrun reminds me of xclock:

It is all about measuring time using useless clocks. Script takes a system time and displays any given clock in a rather “static” way. You can choose between analog, small digital and big digital clock. And when playing with the time, you can also learn something new.

Click through to see how to make an analog clock plot in R, and then try it again with a digital clock.

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Creating a Distributed Availability Group in Azure via Terraform

Sandeep Arora has some scripts for us:

To create a distributed availability group, you need two availability groups (AG) each with its own listener, which you then combine.In this case, one availability group is on-premises and the other needs to be created in Microsoft Azure. This example doesn’t cover all of the details like creating an extended network setup between on-premises network and Azure or joining Azure active directory domain services to and on-premises forest; instead, it highlights the key requirements for setting up the availability group in Azure and then configuring the distributed AG between the on-premises availability group (represented as AOAG-1) and the Azure availability group (represented as AOAG-2).

Click through for the preparations you need in place and a set of scripts to do the work.

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Slot Machine Company Data Breach

Jonathan Greig reports on a data breach:

Nevada Restaurant Services (NRS), the owner of popular slot machine parlor chain Dotty’s, has disclosed a data breach that exposed a significant amount of personal and financial information. 

In a statement, the company confirmed that “certain customers” were affected by the breach and explained that the information includes Social Security numbers, driver’s license numbers or state ID numbers, passport numbers, financial account and routing numbers, health insurance information, treatment information, biometric data, medical records, taxpayer identification numbers and credit card numbers and expiration dates.

I don’t normally link to data breaches too often because if I did, this site would be renamed to Curated Data Breaches given how frequently they occur. But what I want to know is, why in the world does a slot machine company have passport numbers, health insurance information, and medical records? What are they doing with that information? Slot machines are pretty simple: put quarter in, watch the screen light up and speakers make a bunch of happy noises, repeat until you run out of quarters. Unless there’s some sort of business arrangement where they put slot machines in the Nevada hospitals…

Also, the fact that credit card numbers and expiration dates were lost makes me wonder if they were actually PCI compliant.

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Azure Monitor Logs in Azure Data Studio

Julie Koesmarno has a new extension for us:

The Azure Monitor Logs extension in Azure Data Studio is now available in preview. The extension is supported in Azure Data Studio August 2021 release, v1.32.0.

Administrators can enable platform logging and metrics to one of their Azure services such as Azure SQL and set the destination to Log Analytics workspace. By installing native Azure Monitor Logs extension in Azure Data Studio, users can connect, browse, and query against Log Analytics workspace. Data professionals who are using Azure SQL, Azure PostgreSQL, or Azure Data Explorer in Azure Data Studio can access the data in the Log Analytics workspace for diagnosis or auditing in that same development environment. This native Azure Monitor Logs extension allows Azure service customers to also author notebooks with Log Analytics kernel, all equipped with Intellisense.

Click through for examples of how to use this.

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Data Personas and Data Platform Rights

Craig Porteous wants us thinking about roles and permissions:

There are a great number of factors that contribute to an organisation’s data maturity, both technical and non-technical. The non-technical factors often have the biggest impact however. Such as how open to change the business’s upper management is, how much data is embraced by department and team leaders, and the training and support provided to utilise new technologies. All of these factors set the expectation and appetite for change within the business much more than the role out of a new product or technology.

Data Personas are one such area that contribute greatly towards Data Maturity as they define responsibility and access beyond the roles and job titles of team members. Individual team members may fit multiple personas or none at all. There are five core Data Personas that need to be established within an organisation for effective data governance and management with some additional personas on the periphery that can map a bit more to specific technical roles. The number of personas will vary depending on the maturity of the organisation’s data platform and their use of data but the core personas are relevant to all organisations.

Click through for an example set of personas and what kinds of rights they would need, broken down in a matrix of environment and data layer.

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