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In this article authors focused on the role of decision intelligence in closing the “last mile” gap between current technologies and the value large organizations seek to extract from their data analytics investments. By diwo.ai.

Decision intelligence (DI) is the ability to use relevant and available data to identify and explain optimal actions that improve business outcomes.

We live in a world where there is so much data available, and it is growing non-stop. By 2025, there will be ~ 128 zbs of data. The average employee today is simultaneously engulfed by data and yet unable to find the most important data to make the best decisions in real time. So businesses have data, but lack insights to efficiently bridge the gap from data to decisions—what is commonly referred to as the “last mile of analytics challenge.” Companies won’t realize the full promise of data analytics until they operationalize the “last mile” step where insights become actionable. The path to ROI with analytics is better decisions, not better dashboards.

The article is split into:

• Can decision intelligence solve the last mile of analytics challenge?
• How can decision intelligence help more people improve decision-making in the daily routine of their jobs?
• Where should decision intelligence be used?
• How does decision intelligence fit into the modern data stack?

In its simplest form, a modern data stack encompasses an ingestion tool, a warehousing tool, a transformation tool, analysis and model building tools and the “decision” layer built on the advanced analytical capabilities of decision intelligence. Each of these layers play a key role in an organization’s ability to get actionable insight from vast amounts of data and ML models, develop recommendations for action and accelerate decision-making. Good read!

Researchers are developing an anti-eavesdropping quantum network. By Technische Universitat Darmstadt.

While quantum computers offer many novel possibilities, they also pose a threat to internet security since these supercomputers make common encryption methods vulnerable. Based on the so-called quantum key distribution, researchers at TU Darmstadt have developed a new, tap-proof communication network.

The new system is used to exchange symmetric keys between parties in order to encrypt messages so that they cannot be read by third parties. In cooperation with Deutsche Telekom, the researchers led by physics professor Thomas Walther succeeded in operating a quantum network that is scalable in terms of the number of users and at the same time robust without the need for trusted nodes.

So far, such quantum key methods have been technically complex and sensitive to external influences. The high stability of the transmission and the scalability in principle were successfully demonstrated in a field test together with Deutsche Telekom Technik GmbH. As a next step, the researchers at TU Darmstadt are planning to connect other buildings in the city to their system. Interesting read!

How MLOps helps across all stages of ML project. By Alexey Grigorev.

It’s a common misconception that MLOps is solely about the tools we use for deploying models and preparing the infrastructure for it. Partly it is, but it’s not the whole story – there’s much more. In this post, I’ll break down a machine learning project into several stages and explain how MLOps helps at each of them.

Source @towardsdatascience.com: https://towardsdatascience.com/mlops-in-10-minutes-165c746a9b8e

MLOps is a new topic and there’s no consensus on what it is or what it is not. In this post, author will share his personal take on it. You don’t have to agree with it, but he hopes it’ll still be useful.

The article pays attention to:

• What is MLOps
• Train stage
• Experiment tracking
• Training pipelines
• Operate stage
• Deployment
• Model monitoring
• People, processes and best practices

In this article, we only scratched the surface. We discussed what MLOps is and looked at the helicopter view of the process. We broke down the process into 3 stages: design, train and operate. Good read!

When the person at the top is malignant and self-serving, unethical behavior cascades through the organization and becomes legitimized. By Lee Simmons.

You end up with these individualistic cultures with no teamwork and low integrity. We’ve documented this in a bunch of Silicon Valley tech firms.

Charles A. O’Reilly

What traits do we look for in our leaders? Ask someone what distinguishes a forceful leader, in business or politics, and they’re likely to mention self-confidence and charisma. Great leaders, we say, are bold and strong-willed. They have a vision for creating something new or remaking a company or a country. They challenge conventional wisdom and are slowed by neither self-doubt nor criticism.

The article explains:

• Why do we empower them?
• Tallying the damage
• Follow the trail

True narcissists, O’Reilly says, are self-serving and lack integrity. “They believe they’re superior and thus not subject to the same rules and norms. Studies show they’re more likely to act dishonestly to achieve their ends. They know they’re lying, and it doesn’t bother them. They don’t feel shame.” They are also often reckless in the pursuit of glory – sometimes successfully, but often with dire consequences. Interesting read!

Man-in-the-middle (or MitM) attacks can occur when an attacker has the ability to intercept communications over the network. This allows the attacker to read – and potentially modify – these communications. By Rob Behnke.

MitM attacks rely on an attacker’s ability to intercept, read, and modify network traffic. While a user has limited control over how their traffic flows over the Internet, they can take steps to make MitM attacks more difficult to perform. For example, the use of a virtual private network (VPN) when connected to public Wi-Fi networks helps to protect against traffic interception by a malicious wireless access point.

TLS is designed to help maintain the confidentiality and integrity of network traffic. However, the system has some weaknesses that can make it vulnerable to attack.

One of the biggest limitations of TLS is that it only proves that a user is connected to a legitimate web server for the URL that they are visiting. If the client is tricked into visiting a malicious URL via a phishing attack, then all TLS does is protect the user’s connection to the attacker’s server.

A MitM attack is mainly a threat when cybersecurity best practices aren’t followed. The use of TLS whenever possible and a VPN when connected to untrusted public networks dramatically reduces the risk of MitM attacks. Good read!

To succeed as a customer-centric team, building and honing digital optimization skills is crucial. Here are the skills to focus on.. By Will Watkinson. Digital optimization is critical for driving sustainable business growth with product data. But what does it mean to operate with digital optimization? By Mallory Busch.

A digitally optimized company empowers every customer-centric team to explore product data, gather technological insights, and take immediate action to drive toward business outcomes. Oftentimes, these identified outcomes are centered around driving long-term customer loyalty and value.

The article then delves on these skills:

• Customer-centric mindset
• Product-led mindset
• Data-driven mindset
• Agility
• Collaboration
• Change management

Digital optimization requires companies to be able to keep up with constantly changing demands and take quick action based on insights. Businesses will often use an ecosystem of integrated tools to provide access to product data across various functions. Tools such as Braze and Amplitude are good examples. Nice one!

Companies organize and automate their internal processes with a multitude of business systems. Since companies function as a whole, these systems need to be able to talk to one another. At Shopify, we took advantage of Ruby, Rails, and our scale with these technologies to build a business system integration solution. By Will Watkinson.

The article then walks you through:

• The modularization of business systems
• Organic integration
• Integration platform as a service
• Building on Shopify’s stack
• The design priorities
• Implementation

The transition from monolithic to modular architecture doesn’t remove the need for interaction between modules. Maintaining well-defined, versioned interfaces and integrating with other modules is one of the biggest costs of modularization. In the business systems space, however, it doesn’t always make sense for vendors to take responsibility for integration, or do it in the same way. Good read!

There is a major shortage of cybersecurity professionals, with the equivalent of a major city worth of workers missing from the workforce. (ISC)2, the world’s largest professional organization for cybersecurity workers, estimates in the paper linked above that the cybersecurity workforce will have to increase by 65% to meet demand. By Nils Gerhardt.

Furthermore, we have seen increased cybersecurity threats and reduced employee training due to the COVID-19 pandemic, reducing the ability of professionals and new entrants into the field to train. Most worrying, new technology threatens to make existing cybersecurity skills obsolete and renders many of the forms of protection they rely on null.

The article discusses following:

• A lack of cybersecurity skills
• Emerging threats
• Preparing for a post-quantum world

It is apparent that the cybersecurity workforce will need to increase. Therefore, a large-scale realignment aimed at getting more qualified workers into the industry, helping decision-makers understand the issues and preparing the current and future workforce for a quantum computing age. Good read!

The main misunderstanding, and source of the issues, is related to deciding on the stale data. It brings uncertainty and the need for workarounds. It’s a common mistake to use tools like Kafka and Pulsar for event stores, but they are not. You don’t have basic guarantees for optimistic concurrency checks. By Oskar Dudycz.

TLDR: We assume that conflict situations will be rare. A conflict arises when two people try to change the same record at the same time. When this happens, we will only allow the first person to update the state. All other updates will be rejected. For verification, we use a record version that changes with each save.

All of the event stores that I know support strong consistency on appends, and optimistic concurrency. Most guarantee global ordering. Some have a built-in idempotency handling. All of that helps to reduce those issues. In Event Sourcing, events are the state.

The events are the source of truth, only if you’re using them in the write model as a basis for the state rehydration. If you’re using a materialized view, even though it’s built based on events, then you outsourced the truth to other storage. If you’re using a pattern that means you’re just using events to build up the materialized view you use for the write model logic, that can lead to using Event Streaming tools like Kafka, Pulsar, etc. And, as stated in the article, this is a dead-end. Read more in How to get the current entity state from events?.

Event Sourcing by itself doesn’t directly relate to eventual consistency, type of storage, messaging, etc. Those are implementation details and tradeoffs we’re choosing. Each storage solution has its patterns and anti-patterns: relational databases have normalization, document databases are denormalized, key-value stores have strategies for key definition. Event stores also have their problems. Super interesting read with plenty links to further reading in the topic!

SwiftUI is Apple’s new declarative framework for building user interfaces for all Apple devices. This framework can be broken down into two essential components: views and state. By Amisha I.

State management is an integral part of SwiftUI development, and there are many different ways of working with the state. In which State represents the data associated with a view. In this article we are going to learn about a state holder to separate business logic from UI components. ViewModel has a longer lifecycle than the view so ViewModel can preserve its state across UI changes.

For simplicity, author divided this post into 3 sections:

• Add data layer – Responsible for fetching data from API
• Add ViewModel – Responsible for managing the state of the screen
• Add View – Actual UI representation that users will see

This is one of the ways to manage the state, however, you should explore other options as well once you are familiar with these basics. Good read!