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Now more than ever, startups and corporates are looking for ways to run lean. There is pressure to make cuts to staff and outsource when possible, and this has led to a trend of hiring virtual CFO services over the more traditional in-house full-time chief financial officer (CFO). Written by Dave Robinson.

Page Speed performance is incredibly important. Every millisecond counts, and you will lose customers, leads and SEO ranking if you have a slow site. But how much business will you lose? Should I make my website faster? Do I have a business case? Can I spend $10,000 to make my site load faster?

The summary of what you will get:

• all variables and code to implement in Google Tag Manager, so you won’t have to think (and click 632 times to create all the variables)
• the SQL to nicely model the data in an tidy non-nested table
• a step by step guide on how to set things up and use the data

This is step by step tutorial with all the steps explained and accompanied by clear screen shots. Solution includes (amongst others):

• How to set up a Google Cloud project and enable billing
• Create a Google Analytics App+Web property (via a Firebase Analytics project)
• Enable the streaming of Firebase data to Big Query
• Create / import a Google Tag Manager container and include it on your web site
• Set up data collection tag + variables in Google Tag Manager

… and more. You don’t have to stay in the Google stack. You can pull data in R to mode page speed in relation to web site behaviour. Excellent!

Now more than ever, startups and corporates are looking for ways to run lean. There is pressure to make cuts to staff and outsource when possible, and this has led to a trend of hiring virtual CFO services over the more traditional in-house full-time chief financial officer (CFO). Written by Dave Robinson.

You, your board and your investors are probably asking some questions like:

• How do we run on as little executive overhead as possible without missing out on making the right decisions?
• What services do virtual CFOs offer and what will we need to find elsewhere?
• How does working with a virtual CFO actually happen? How often will they be available? How will they deliver reports?
• And, of course, How much do part-time CFOs cost?

The artticle covers some of the more specific deliverables, and captures some of the broader benefits of virtual CFO services. A CFO can identify and manage bookkeeper/controller to produce reliable data and interpret the results, providing insight to help steer the ship toward your stated goals. Nice read!

A mental model reflects an individual’s beliefs, values, and assumptions. As those are internal, we need to somehow express them in order to learn and improve. Causal Loop Diagram (CLD) is a powerful technique from Systems thinking. By Yi Lv

Models created using CLD often reflect the mental models of people creating them. We could explore different mental models by simply doing advocacy and inquiry with CLD. Balancing advocacy and inquiry is one key practice for the discipline of mental models, among the five disciplines from the classical “The fifth discipline” book.

The article provides few examples when author was doing system modeling for the number of backlogs and its impact on adaptiveness. For some organizations, strong reliance on business feedback increases the motivation to adapt, while the limited broad learning due to specialization decreases the ability to adapt. Good read!

React is a popular JavaScript library developed by Facebook for building user interfaces. It uses the concept of Virtual DOM to render Elements into the browser DOM because it is a popular belief that manipulating the browser DOM directly can be very slow and costly. By Temitope.

Well according to React, Hooks are functions that let you “hook into” React state and lifecycle features from function components. Before the arrival of Hook, state and React lifecycles can only be used in a class component. Starting from version 16.8, React rolled out a lot of features that enable developers to hook into a React state without having to write a single class component.

You will be building a simple CRUD blog app where a user can create a post, read the post, update post, and delete the post without making any API request to the server.

The article is split into:

• What are Hooks in React?
• What we’re building
• The Setup
• Building Our App
• JSX

… and more. All the code in the tutorial is well explained and documented and you will get link to GitHub repository as well. Great!

How (not) to put your APIs in a freezer while implementing a Frankensite or an API Ghosttown. In this article we will investigate developer portal anti-patterns – common solutions to developer portal problems where the solution is ineffective and may result in undesired consequences. By Diliny Corlosquet.

Anti-patterns differ from bad practices when:

• It is a common practice that initially looks like an appropriate solution but ends up having bad consequences that outweigh any benefits.
• There’s another solution that is known, repeatable, and effective.

Regardless of the route taken to build a devportal: these anti-patterns occur as a direct result of tight deadlines, inadequate planning, or when the conceptualization of the devportal is oversimplified and underestimated.

The article then goes and describes following:

• How to (over) simplify a developer portal
• The anti-patterns of developer portals
  • API Freezer
  • Frankensite
  • API ghost town
  • Tyrannical toolchain

Assumptions that a developer portal is only for developers will lead down these routes. These types of sites also occur when one department creates a solution for multiple without taking into consideration that people of varying technical backgrounds will have a role to play. Good read!

For some time now, 5G has been associated with the promise of new digital applications and services that come with a hyper-connected life. We have seen that this new technology, which provides “perfect” connectivity, creates new value for both us as individuals and to industries and enterprises. By Balaji Ethirajulu.

Augmented and virtual reality (AR and VR) are two technology concepts providing significant benefits in this new digital reality. These technologies open new ways of working in areas such as manufacturing, gaming, media, automotive and healthcare, allowing for both increased productivity and completely new user experiences. In the Ericsson ConsumerLab merged reality report, 7 out of 10 early adopters expect VR and AR to change everyday life fundamentally.

The article describes:

• Technologies driving the 5G evolution
• 5G business models
• AR/VR use cases at home and enterprises
• Enabling AR/VR experiences with 5G and edge compute
• Our solution: Ericsson Private networks

While many of us see AR and VR technologies mainly used for gaming, in reality, many industry verticals are looking at these technologies as game changers. Good read!

Written by James Long this blog post focuses on namecheap.com top five tips to help you maximize your productivity when mapping your day working from home. Ask anyone in a 9-5 office job, and the chances are they quietly yearn for that trademark flexibility of the home worker, self-employed, or business owner.

But one of the toughest challenges, particularly when working at home, often alone, is keeping yourself motivated throughout the whole day. Suddenly the 9-5 you had seems comparatively productive — the whole day was carefully mapped out, and you got stuff done. Whether that was true productivity is another thing; when the lunches, coffee breaks and commute (oh yeah — remember the commute) are considered, and those hours where you were just filling time, you realize it was perhaps the illusion of productivity, rather than productivity itself.

Top 5 tips for maximizing productivity:

• Choosing location
• Setting goals
• Creating variation
• Distractions & breaks
• Exercise

Without your commute, it’s easy to become stuck inside. Aside from obvious health implications, you might find that you find it more difficult to sleep. So, it’s important to use up that energy. Great read!

How to learn to unify Google Sheets, Excel, and CSV files – a code-along guide. By Fabian Bosler.

Python is often called a glue language. This is due to the fact that a plethora of interface libraries and features have been developed over time — driven by its widespread usage and an amazing, extensive open-source community. Those libraries and features give straightforward access to different file formats, but also data sources (databases, webpages, and APIs).

This story focuses on the extraction part of the data. Next week’s story will then dive a little deeper into analyzing the combined data to derive meaningful and exciting insights.

What you will learn:

• Extracting data from Google Sheets
• Extracting data from CSV files
• Extracting data from Excel files

As this article is intended as a code-along article, you should have your development environment (recommended: Jupyter Notebook/Lab) set up and start a new Notebook. You can find the source code and files in provided GitHub repository. Great resource!

Haridas N is author of this article about data pipelines and how machine learning (ML) helps businesses manage, analyze, and use data more effectively than ever before.

ML identifies patterns in data through supervised and unsupervised learning, using algorithms to get actionable insights. Recommendations in travel, shopping, and entertainment websites are typical examples, which use consumer data to make personalized offerings.

The article main parts are:

• Data pipeline – an overview
• Data collection and cleansing
• Storage Layer
• Feature extraction for different models
• Model design and Training
• Serve trained Model

Data Pipelines can be broadly classified into two classes:

Batch processing processes scheduled jobs periodically to generate dashboard or other specific insights

Stream processing processes / handles events in real-time as they arrive and immediately detect conditions within a short time, like tracking anomaly or fraud.

A solid data pipeline holds the promise of transforming the dark-data hidden in silos. Having a flexible, efficient and economical pipeline with minimal maintenance and cost footprint allows you to build innovative solutions.

In this tutorial, you will learn how to implement and train autoencoders using Keras, TensorFlow, and Deep Learning. Author discusses what autoencoders are, including how convolutional autoencoders can be applied to image data. Also more about the difference between autoencoders and other generative models, such as Generative Adversarial Networks (GANs). By Adrian Rosebrock.

Typically, we think of an autoencoder having two components/subnetworks:

• Encoder: Accepts the input data and compresses it into the latent-space. If we denote our input data as x and the encoder as E, then the output latent-space representation, s, would be s = E(x).
• Decoder: The decoder is responsible for accepting the latent-space representation s and then reconstructing the original input. If we denote the decoder function as D and the output of the detector as o, then we can represent the decoder as o = D(s).

You can thus think of an autoencoder as a network that reconstructs its input! To train an autoencoder, we input our data, attempt to reconstruct it, and then minimize the mean squared error (or similar loss function). Ideally, the output of the autoencoder will be near identical to the input.

To learn more follow the link to the article. Nice one!