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Data Engineering

Up to now in this Course, we have been focusing on Software Engineering:
What is Software?
Algorithms to run Processes.
The other side of the field in building Business IT Systems, which is our End Goal, is

DATA ENGINEERING

What are data contracts and how do they relate to the USE of AI to build Management Information Systems

Data contracts are agreements that codify data needs and schemas upfront to ensure transparency and build trust between teams (
.)
They are not in-depth legal documents, but rather a way to establish clear expectations for data usage and to identify who owns the responsible to produce the data and what the correct usages of the data are.
In the context of AI and management information systems, data contracts can help ensure that the data used to train AI models is accurate and reliable (
.)
By using AI to analyze data contracts, organizations can also identify patterns and extract key variables to improve contract management processes (
.)
Microsoft's Cloud Adoption Framework provides guidance on how to create and manage data contracts

What is the role of data contracts in building Management Information Systems

Data contracts play an important role in building Management Information Systems (MIS) by ensuring that the data used to train AI models is accurate and reliable.
They are agreements that codify data needs and schemas upfront to ensure transparency and build trust between teams
.
In the context of MIS, data contracts can help organizations establish clear expectations for data usage and improve contract management processes
.
By using AI to analyze data contracts, organizations can identify patterns and extract key variables to improve the accuracy and efficiency of MIS
.
A contract data management system, which is part of contract management software, can also help create a single source of contract information and provide real-time access to key data
.
Using data contracts in building Management Information Systems (MIS) has several benefits. Firstly, data contracts ensure that the data used to train AI models is accurate and reliable, which improves the accuracy and efficiency of MIS
. Secondly, data contracts help establish clear expectations for data usage and improve contract management processes, which can save time and reduce the risk of errors
. Thirdly, data contracts can help build trust between teams by ensuring transparency and accountability
. Finally, by using AI to analyze data contracts, organizations can identify patterns and extract key variables to improve the accuracy and efficiency of MIS
. Overall, data contracts are an important tool for organizations looking to build effective and reliable MIS.
Data contracts improve data tracking in building Management Information Systems (MIS) by ensuring that the data used to train AI models is accurate and reliable. Data contracts codify data needs and schemas upfront to ensure transparency and build trust between teams
. By establishing clear expectations for data usage, data contracts can help improve contract management processes and save time
. In the context of construction management, information technology can help track data efficiently, and data contracts can help ensure that the data being tracked is accurate and reliable
. By using AI to analyze data contracts, organizations can also identify patterns and extract key variables to improve the accuracy and efficiency of MIS
. Overall, data contracts are an important tool for improving data tracking and ensuring the reliability of MIS.

AI First Paradigm

Just as up to now, in the technology/programming training, we have a line item in the Course Outlines to take a "MOBILE FIRST" paradigm, meaning whatever you program, make it focused on working well on a mobile device.

Case study from my business courses: Sears Canada went bankrupt because they were late to the game in terms of firstly, getting a website ecommerce presence up and going, and secondly, because they did not make their mobile app device access pleasant and user-friendly. Same for Yahoo: they did not make their search to be mobile access centered. (including things like providing APIs for other technology vendors to leverage into Yahoo and thereby indirectly affliate with them).

The relevance here is: Now we should focus on making our IT applications "AI First". (I came up with this myself although I have not done a literature search to see who else might be using that term.). Meaning: We embed AI into everything we do. I was discussing these thoughts with my MAD 5274 class and the hair on the back on my neck stood up when in Capstone presentations today, one of the teams proudly showed me how they were building the scaffolding of AI and ML processing into their Mobile App so the AI can leverage the customer experience by learning what the user is doing with the App to predict what they will want next, even before the user realizes it.
Here is that team's work:
In which they presented tooling the Mobile App to make calls to ChatGPT to advise and curate recipe ideas for users, based on things that the user HAD NOT YET THOUGHT OF TO BE INTERESTED IN (this is the unique use case of AI).
Inspired by an In Class Study we did from one of my LINKED BLOGS: ​
AI will be embedded into everything else: Data Analytics is an early example.
In the next 10 years, businesses will rise and fall in accordance with how good a job they do of going AI-first.
Wouldn't that be an interesting concept to present to our Industry partners to demonstrate our capacity for Thought Leadership.
1980s: Databases, Office productivity software and Local Area Networks.
1990s: The Internet. Lans became world-spanning.
2000s: Social Media - Smart Phone Fusion.
2010s: Big data and the development of the Global Dataplex
2020s (now) AI is the new IT thing, encompassing all previous technologies. AI can predict what we don't yet realize we want.
This is the AI First Paradigm.
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In today's competitive market, creating a mobile app that delivers an exceptional user experience is crucial for success. With the ever-increasing number of apps, users have a vast array of options to choose from, making it essential for developers to create engaging, user-friendly apps that stand o
www.linkedin.com
Back in 2017 when I starting teaching at the college level, I was teaching these concepts: Here is some of the material I developed when I started teaching college level at Pures back then: There were no books or other formal materials so I scoured websites and made it up as I was going along.
All of this came out of the MIS Management Information Systems of the 1990s, when numerous small databases were merged together on Corporate Lans and then the Internet. The history of Technology is my hobby. Here is a document I put together outlining these developments:
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coda.io
The early forerunner to Chat GPT was IBM Watson, a freely available IBM service that provided primitive (compared to today) access to AI experimentation. That was for a couse in Business Analytics in which I had those students use Watson to do research for their course project:
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https://www.dropbox.com/scl/fi/v8sg5frc93f6c687r3rzq/A.-Decision-Science-Building-Decision-Support-Systems.pptx?dl=0&rlkey=iody96spr7i739fx1f8d8i2ip
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