Earlier this month, I hosted March 2023’s T-SQL Tuesday with an invitation concerning the ongoing Microsoft and OpenAI partnership:
What is on your wishlist for the partnership between Microsoft and OpenAI?
What follows is some commentary on, and links to, each of the responses.
Chad Callihan
Chad’spost considers potential PowerShell-OpenAI functionality, which would write scripts in response to user prompts. PowerShell is a mainstay of many data professionals, enabling modules like dbatools, Pester and the AWS, Azure and GCPSDKs. An AI with access to the PowerShell Gallery would be very helpful.
Chad also points out some security concerns linked with ChatGPT use, which are good advice in general:
Chris’spost considers an AI model for file ingestion. Data pipelines frequently rely on source data with specific types and layouts. Unfortunately, source data can change between ingestion times.
At best, this breaks pipelines and causes problems and downtime for data teams. At worst, incorrect data is ingested causing potential business and customer detriment.
A no-code AI model would save hours of work if it considered previous source data and could make decisions like “This column is formatted as VARCHAR, but yesterday it was DATETIME2 and has hyphens in the right place, so I’ll CAST it as DATETIME2 today and raise a warning in the log.”
Rob Farley
Rob’spost was partially written by ChatGPT! Rob takes a pragmatic approach to AI’s progress and draws a Clippy analogy. I really want to see this AI family tree now.
ChatGPT suggests that it can help with Excel formulae, SQL Server optimization and PowerPoint visuals. It also wants to democratize technology interaction and remove traditional barriers to entry.
Steve Jones
Steve’spost imagines the next generation of AI personal assistant. One that can:
Learn from the user and correct common errors in all applications.
Suggest code optimizations in a variety of IDEs and languages.
Learn the user’s schedule and create automated calendar events and reminders.
Recognise repeat tasks and create related automation.
Summary
In this post, I wrote a round-up of the community responses to my March 2023 T-SQL Tuesday #160 invitation: Microsoft OpenAI Wishlist.
Thanks to everyone who contributed to my first T-SQL Tuesday invitation. It was great to read your responses! Anyone interested in hosting future events should contact Steve Jones.
If this post has been useful, please feel free to follow me on the following platforms for future updates:
Artificial Intelligence has been a big deal in recent months. One of the main drivers of this has been OpenAI, whose DALL-E 2 and ChatGPT services have seen extraordinary public interest and participation.
Microsoft has been one of OpenAI’s most prominent supporters. In July 2019 Microsoft invested $1 billion in OpenAI and became their exclusive cloud provider.
However, Power BI is reliant on user skill levels. Like all data visualization tools, Power BI can create bad dashboards in the wrong hands. Like, really bad. Dashboards can suffer from several problems that make them useless at best and misleading at worst.
"Improve my annual sales dashboard"
>> I have changed the pie chart showing 12 team members to a bar chart, as this will improve the visualization's legibility.
Azure IAC AI Assistant
IAC (Infrastructure As Code) has revolutionized the public cloud industry, bringing with it benefits like:
Automated, faster deployments.
Repeatable and consistent deployments.
Self-documenting infrastructure.
But IAC also presents challenges:
IAC scripts rely on the skills of the engineer writing them.
It’s not easy to incorporate existing infrastructure.
ChatGPT could resolve many of these problems, turning infrastructure creation into a conversation. It could, for example:
Create infrastructure based on non-technical requests:
"Make me what I need to start a blog."
>> I have created a LAMP stack on a virtual machine in your default region. Your access details are here:
Username: Username
Password: Password
Learn current infrastructure usage patterns and create optimisations for busy and quiet periods.
Spot potential conflicts and step in to prevent data loss or downtime.
Make existing infrastructure faster, cheaper or more performant without the need for manual refactoring.
Resolve problems like high latency, failing connections and unexpected cost increases:
"Why is my web app generating errors?"
>> One of your virtual machines does not allow connection requests from CIDR range 10.01.10.01/28. Do you want me to fix this?
"Yes please."
>> I have now amended virtual machine MYAPP001's Network Security Group to accept incomming connection requests from CIDR range 10.01.10.01/28.
Summary
In this post, I hosted March 2023’s T-SQL Tuesday with an invitation concerning the ongoing Microsoft and OpenAI partnership. I look forwards to reading everyone’s responses!
If this post has been useful, please feel free to follow me on the following platforms for future updates:
Anyone following my Instagram will have seen that I attended the AWS Summit London 2022 event in April. This was my first AWS event, and I had a great time watching the presentations, taking in the atmosphere and finding things that a magnetic shark could stick to.
Besides stickers and badges, I left the event with pages of notes and photos of slides that fell roughly into two lists:
Consider for work
Consider for me
I’ve done the work list, so it’s time for mine! This post has two halves. Firstly, I’ll talk about some of the AWS services I want to try out on the blog over the next few months.
Then, in the second half, I’ll talk about some of the third party presentations that introduced me to interesting things that I hadn’t heard about before.
In this section, I’ll talk about some of the services mentioned in the AWS Summit London 2022 sessions that I want to try out over the next few months.
I was impressed with how quick and simple the SDK is to use, and have a few ideas for it as part of some Python ETLs and IoT functions I want to try. In addition, I can create and then re-use common monitoring modules to save myself some time in future.
Amazon Timestream is a fast, scalable, and serverless time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day up to 1,000 times faster and at as little as 1/10th the cost of relational databases.
Some time soon I’m hoping to try out a Raspberry Pi project that uses a temperature sensor. Timestream looks like a good fit for this! It’s built with IoT in mind, is serverless and offers built-in analytics. In addition, it offers integrations with Amazon Kinesis and Grafana, so it sounds simple to get off the ground.
AWS Data Exchange makes it easy to find, subscribe to, and use third-party data in the cloud.
After you’ve subscribed to a data product, you can use the AWS Data Exchange API to load data directly into Amazon Simple Storage Service (S3) and use a range of AWS analytics and machine learning (ML) services to analyze it.
One of the challenges of trying out services aimed at big data is a lack of big data.
Sample databases like Northwind, AdventureWorks and WideWorldImporters have been around for a while, helping generations of people learn their craft. However, Northwind was intended for SQL Server 2000. And although WideWorldImporters is more recent it’s a bit limited by modern standards.
AWS Data Exchange offers a variety of modern Data Products via the AWS Marketplace. Currently, there are over 3500 Data Products and almost half of them cost nothing to access. So lots to use for potential EMR, Glue and SageMaker projects!
The AWS DataOps Development Kit is an open source development framework for customers that build data workflows and modern data architecture on AWS. Based on the AWS CDK, it offers high-level abstractions allowing you to build pipelines that manage data flows on AWS, driven by DevOps best practices.
The DDK joins the CDK as something I want to try out. I’ve not done anything with infrastructure as code on the blog yet. However, the CDK sounds like a good place to start, and the DDK could quickly spin me up some infrastructure to use with some Data Exchange data.
You will learn about AWS observability functionalities on Amazon CloudWatch, AWS X-Ray, Amazon Managed Service for Prometheus, Amazon Managed Grafana and AWS Distro for OpenTelemetry (ADOT). The workshop will deploy a micro-service application and help you learn monitoring.
In this section, I’ll talk about some of the third party presentations that introduced me to interesting things that I hadn’t heard about before.
Cazoo’s Serverless Architecture
Cazoo‘s Engineering Coach Bob Gregory spoke about their use of AWS serverless technologies including Lambda, DynamoDB and Athena. As a result, Cazoo was the first to market and could scale quickly in response to rapid customer demand.
This was my first time hearing about Cazoo, and Bob turned a very business-oriented presentation into a chat with some mates at the pub. He has a great speaking style, an example of which is here:
Amazon published a press release about Cazoo on the day of the Summit. It details Cazoo’s current and future relationship with AWS and includes Cazoo’s plans to integrate various AWS machine learning tools. Examples include Textract for paperwork processing and invoice management and Rekognition for inventory handling and rapid image and video analytics.
And speaking of analytics…
EMIS Group’s Data Architecture
EMIS Group‘s CTO Richard Jarvis spoke about how they use various AWS services to ingest, analyse and present health care data. During the 2020 Pandemic, they were able to quickly analyse national COVID-19 data and provide clinical research about topics including transmission, treatment and vaccination.
EMIS Group’s data security includes a Data Mesh architecture, which separates data producers from data consumers. Meanwhile, AWS IAM handles the security of their applications by controlling how users access them and how they interact with each other.
As a result, EMIS Group can ensure that the right applications are accessible by the right people, and that sensitive and personal data is stored appropriately and in line with GDPR.
Ocado’s Fulfilment Robots
Ocado‘s Chief Technology Officer James Donkin and Chief of Advanced Technology Alex Harvey spoke about the use of AWS at their fulfilment centres. Ocado has made a name for itself in the field of robotics and has used this technology to drive efficiency and innovation.
That video is from 2018 and a lot has changed since then. This year Ocado have begun upgrading to their new 600 Series fulfilment robot, pictured here:
Wait. That’s a Borg Cube. Hold on.
YOU WILL BE REFRIGERATED
Alex and James talked about the challenges of operating thousands of robots, and how AWS help them innovate and scale while maintaining low latency and cost. Ocado deploys microservices and web applications to AWS, which the robots rely on for communication and navigation.
In this post, I discussed the main takeaways from my recent visit to the AWS Summit London 2022 event. I talked about some of the services I want to try out on the blog over the next few months, as well as some of the third party presentations that introduced me to interesting things that I hadn’t heard about before.
In conclusion, I had a great time at the summit! I came away with a lot of good ideas and had some great conversations. Hopefully, I’ll be able to go back next year!
