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Sunday, 14 October


Data Quality in the era of A.I. - Medium

Data quality in the era of AI

Data quality is of critical importance especially in the era of Artificial Intelligence and automated decisions. Do you have a strategy?

Database clipart from dumielauxepices.

Data-intensive projects have a single point of failure: data quality

As the director of datamine decision support systems, Ive delivered more than 80 data-intensive projects across several industries and high-profile corporations. These include data warehousing, data integration, business intelligence, content performance, and predictive models. In most cases, data quality proved to be a critical factor for the success of the project.

The obvious challenge in every single case was to effectively query heterogeneous data sources, then extract and transform data towards one or more data models.

The non-obvious challenge was the early identification of data issues, whichin most caseswere unknown to the data owners as well.

We strategically started every project with a data-quality assessment phasewhich in many cases lead to project scope modifications and even additional data cleansing initiatives and projects.

Data quality defined

There are many aspects to data quality, including consistency, integrity, accuracy, and completeness. According to Wikipedia, data is generally considered high quality if it is fit for [its] intended uses in operations, decision making and planning and data is deemed of high quality if it correctly represents the real-world construct to which it refers.

I define data quality as the level of compliance of a data set with a contextual normality.

This normality is set by user-defined rules and/or statistically derived ones. it is contextual, in the sense that rules reflect the logic of particular business processes, corporate knowledge, environmental, social or other conditions. For example, a property of the same entity could have different validation rules in different companies, markets, languages, or currencies.

Modern systems need to become aware of the quality in data I/O. They must instantly identify potential issues and avoid exposing dirty, inaccurate or incomplete data to connected production components/ clients.

This implies that, even if there is a sudden problematic situation resulting in poor-data quality entries, the system wi...

Saturday, 13 October


Merging for what? Bernard Davies asks IN DEFENCE OF YOUTH WORK


Bernard Davies responds to the series of mergers in the youth sector.

The recent BBC documentary on the 2008 collapse of the Royal Bank of Scotland was a stark reminder of how crucial mergers are to the way the neo-liberal global economy operates. Far from small is beautiful, one of its bottom-lines seems to be: the bigger the better otherwise, as RBSs earlier history showed, your business will be seen as insignificant and vulnerable to take-over. Once this gets itself beyond the stage of being the hunted, however, thoughts are then liable to turn increasingly to how to become the predator to the point where, as in RBSs case, the power this brings and the hubris this encourages make taking over others almost an end in itself.

All of which prompted me to wonder whether any of this kind of thinking has driven the youth work fields rush to mergers over the past decade? After all, the BBC programme came within days of the latest such example: the announcement that the Centre for Youth Impact (CYI) a community of organisations that work together to progress thinking and practice around impact measurement in youth work and services for young people- is in effect to take over Project Oracle. This was an organisation which had been describing its purpose as supporting children and youth organisations and funders to produce, use and share high-quality evidence.

Some of the voluntary youth sectors earlier mergers have had much more...


How to setup TinyMCE in your Rails app using Webpack - Medium

The popularity of using Webpack to deal with your assets in Rails is steadily increasing. Getting started is really straightforward. If you are starting a new app, you simply run rails new my_app --webpack and Rails takes care of the rest.

Thanks to the webpacker gem, adding Webpack to your existing application is also pretty uncomplicated. You add the gem to your Gemfile, bundle, and finally install webpacker:

gem 'webpacker', '~> 3.5'
bundle exec rails webpacker:install

This is pretty sweet. Now all you need to do is link your JavaScript pack and the CSS imported in it into the head of your application.html.haml:

<%= javascript_pack_tag 'application' %> <!-- js from app/javascript/packs/application.js -->
<%= stylesheet_pack_tag 'application' %> <!-- CSS imported via Wbpack -->

Once this is done, you are ready to write your modern JavaScript code and make use of all the great libraries out there.

What is tinyMCE?

TinyMCE is a rich text editor in the cloud. To put it simply, its like Word that can be implemented into your app.

The project I am working on uses it to let admins edit the content of the front page. Thanks to TinyMCE, it isnt necessary to build a separate admin interface for that purpose. But the editors usage can be much more versatile. Think, for example, of what Wordpress or Evernote allows you to do thanks to their build in tools.

Example use of TinyMCE. The power is in the users hands now.

Usage via CDN

We originally implemented the editor via CDN (e.g. linking the script in the head of our application.html.haml) like this:

%meta ... <!-- some meta content -->
%title ... <!-- MyApp -->
= csrf_meta_tags
    %script{src: ''}

= stylesheet_link_tag 'application', media: 'all'
= javascript_include_tag 'application'
<!-- the usual body stuff -->

This required adding a file with our customized function in app/assets/javascript/tinyMce.js. Note that we are also using jQuery.

$( document ).on('turbolinks:load', function() {
selector: 'textarea.tinymce',

// some other settings, like height, language,
// order of buttons on your toolbar etc.

plugins: [


Fibonaccis Strange Loop: the beauty of mathematical inception - Medium

Photo by Diana Deaver on Unsplash

Its hard to take an algorithms 101 class without encountering the Fibonacci sequence. The sequence is deeply connected to the golden ratio, which appears over and over again in nature, architecture, art, and the occasional Dan Brown novel. From conch shells to sacred geometry, the Golden Ratio appears to be encoded into many aspects of our universe.

Enumerating everywhere the golden ratio appears would be quite an undertaking, but one of my favorite places where it appears is inside of itself. A recursion inside a recursion; a mathematical inception; what Hofstadter might call a strange loop.

In computer science the sequenceand the different strategies for computing itare also good teaching tools. The Fibonacci sequence can be computed with a clean and simple example of recursion:

As a computer science instructor, I have watched numerous faces scrunch up in confusion when seeing this function for the first time. You can call a function from inside itself? they might ask, How the heck does that work?! Admittedly, I take a small amount of pleasure in my students confusion. Confusion is an integral part of learning, and if a student is never confused I tend to feel that they arent being challenged enough.

One of the most wonderful things about this implementation of the Fibonacci sequence is that the code very closely matches the very definition of the sequence.

The sequence was first described in 1202 by Leonardo Fibonacci. The sequence starts with two 1s, and subsequent digits are computed by adding the previous two digits together. So for the 3rd digit, 1 + 1 = 2, and the 4th digit 1 + 2 = 3, then 2 + 3 = 5 Here are the first few digits:

1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89 

The Python code above reads just like that definitionif n is 0 or 1, return 1, otherwise, return the result of adding fib(n-1) to fib(n-2), AKA return the sum the previous two digits of the sequence. In addition to the sequence itself, Fibonacci discovered the sequences relationship to the golden ratio.

The golden ratio is an irrational number. Like (Pi), it has an infinite number of digits past the decimal and never falls into a repeating pattern. Just like most people remember as 3.14, its good enough to remember the golden ratio as 1.618. Also like P...

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