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Newsletter – January 2020

Published by Ben Morris on

The latest news and articles for January 2020
Project Data Analytics Community Newsletter
January 2020

We produce this newsletter to keep you plugged into the very latest developments, building capacity and understanding within the project delivery community. As part of this quest we are also mobilising our brand new (Project) Data Analyst apprenticeship. It’s equivalent to a foundation degree and will develop a brand new cadre of professionals who straddle the divide between project delivery and data analytics. If you are interested in being one of the very first then get in touch soon; more details can be found here.

Project Delivery
BAM Uses AI to Predict Critical Strength of Concrete
December 2, 2019 – By Unknown
Interesting article detailing how a grant from Innovate UK allowed a collaboration between BAM and Converge to develop an AI concrete strength prediction engine. This example reinforces the positive impact machine learning can have in the construction industry, and also the importance of organisations such as Innovate UK to enable innovation across the economy. Read more …
SAFE: a Collection of Comments From Leading Experts
2019 – By Unknown
An interesting collection of comments on the SAFE framework. Read more …
A Bird’s Eye View on the Agile Forest
November 2019 – By Henny Portman
A great article from Henny Portman on the proliferation of agile frameworks. It’s a superb introduction to all the different methods. Read more …
Project Management Tools: We Compared the Best to Make Your Choice Easy
December 4, 2019 – By Frank Moraes
Its useful to revisit the range of project management tools every now and again. These will proliferate further as AI capabilities develop. What is your strategy for managing them, preventing silos and ensuring that you have data ownership? Read more …
Artificial Intelligence Transforms Oil and Gas
December 20, 2019 – By The Australian
A great article on how Woodside is using AI to develop an in-house learning platform that ultimately can search more than 25 million documents, retrieve content and suggest related information to anyone in the business. Imagine what could be achieved if we plug project delivery data into this capability too. Read more …
Data Analytics
Good Data Starts with Great Governance
November 11, 2019 – By Elias Baltassis , Antoine Gourévitch , and Lucas Quarta
There are several reasons good data governance is important, particularly for compliance and operational reasons. Some industries, such as finance, are subject to strict data governance regulations. With the era of big data upon us, good governance of our data is needed to ensure we reap the maximum benefits. Read more …
Making Python Programs Blazingly Fast
Jan 1, 2019 – By Martin Heinz
Python is often accused of being a ‘slow’ language, however the speed of a specific program is very much dependent on the developer who wrote it. This article outlines some great methods that can be used to improve the speed of your code. Read more …
Gartner Top 10 Data and Analytics Trends
November 5, 2019 – By Susan Moore
This article from Gartner is interesting, mentioning themes such as augmented analytics and graph analytics. Both of these will be crucial within a successful project data analytics-based enterprise. Read more …
Catch Them If You Can: How Leaders in Data and Analytics Have Pulled Ahead
September 2019 – By McKinsey
The start of a new year provides an opportunity to review some great articles from 2019, this one from McKinsey grabbed our attention. Read more …
AI & Machine Learning
Top Minds in Machine Learning Predict where AI is Going in 2020
January 2nd, 2020 – By Khari Johnson
This article includes thoughts from some top machine learning professionals on where AI is heading in the next 12 months. Common themes from these interviews include more accountability of algorithms, better explainability of AI, and a reduction in power needed to create model for areas such as on-device machine learning. This would suggest that a big focus moving forward will be model evaluation in a more broad sense, rather than a particular focus on accuracy. Read more …
The Importance of Edge Machine Learning
January 1, 2020 – By Priya Dialani
An interesting article outlining the advantages of edge processing in reducing latency, improving connectivity and addressing security challenges. Edge computing is especially important for real-time activities, whilst also reducing power utilization and security vulnerabilities. However, one of the challenges of edge computing is balancing keeping data at the edge or storing it centrally, and it will be interesting to see how this is addressed moving forward. Read more …
Productionize a Machine Learning Model with a Django API
Dec 31, 2019 – By Chris
This article provides a tutorial on how to deploy a machine learning model behind a Django API. With all the current tools available it has become more straightforward to build a machine learning model, but deploying it adds another layer of complexity. This tutorial is a helpful guide for any data scientist wishing to deploy a machine learning model of their own. Read more …
Fairness Indicators: Scalable Infrastructure for Fair ML Systems
December 11, 2019 – By Catherina Xu and Tulsee Doshi
Google have recently released a suite of tools that enable regular computation and visualization of fairness metrics to help identify bias in machine learning algorithms. The issue of bias in machine learning has come to light recently, and this looks to be one of the first steps to try and eradicate this from machine learning algorithms. Read more …
Confronting the Risks of Artificial Intelligence
April 2019 – By Benjamin Cheatham, Kia Javanmardian, and Hamid Samandari
Another great article from McKinsey in 2019. This provides an interesting view on how organisastions can mitigate the risks of AI. Read more …
Global AI Survey: AI Prove its Worth, But Few Scale Impact
November 2019 – By McKinsey
This article outlines the work that should be done to scale the impact of AI. Read more …
Robotic Process Automation
5 Robotic Process Automation Trends to Look for In 2020
1st January, 2020 – By Neelesh Kriplani
The RPA market is forecast to expand rapidly in the next 12 months, and over the next year we can expect it to emerge as a more complementary technology and become a more comprehensive offering. This article suggests one of the key trends for 2020 will be RPA driving hyper-automation, where AI and ML are incorporation with RPA resulting in intelligent automation. I would argue that it is too soon for hyper-automation to become mainstream in 2020, but it is definitely an area that will grow over the next few years. Read more …
5 Best Practices for Robotic Process Automation Security
December 10th, 2019 – By Corey O’Connor
This article underlines the importance of security in RPA, ensuring that robots with privileged credentials should follow the same security standards as human users. As organisations rely on RPA more and more, the security of these software robots will become more important. Read more …
Upcoming Community Events
Project:Hack5 is taking place on the weekend of 7th-8th October. Tickets are available of a first come first served basis, so book now to avoid disappointment!
We have some great Project:Meetups lined up for early 2020 across the UK. Check out details of upcoming meetups now!
In 2017 Projecting Success founded the Project Data Analytics CommunityIt is now the UK’s largest community of project delivery and data science professionals. Existing purely for the benefit of its members, it seeks to push the boundaries of project delivery into a whole new realm. We host monthly meetups across the UK and hackathons 3 times a year. For more information visit our website. To receive this newsletter directly to your inbox every month click on the button below.
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