Category: Blog

The most recent ENISA (European Union Agency for Cybersecurity) report on cybersecurity listed supply chain attacks as one of the prime identified threats to the cyber landscape. Cyber attacks are on the rise, alarmingly so, and most recently, some of the most successful attacks have been through the software supply chain. Cybercriminals are aggressively targeting open source software, which is worrying, given how integrated open source software is into the modern business landscape. 

Historical Journey

Introduction Just Imagine you are visiting your favorite online store and the webpage takes 50 seconds to load.

Blockchain’s properties related to security and integrity can open multiple new use cases. But, is this the technology that every project needs to ensure security/integrity? This article is focused on that question.

The introduction of smartphones in the early millennium revolutionized the whole tech world. We witnessed a sudden drift of the user base from desktops and laptops to more compact and palm-sized gadgets where they could do the same day-to-day activities at the touch of their finger from their couch. The portability, compact size, and ease of use demanded the developers to build mobile apps catering to a plethora of requirements.

Blockchain has gained quite a bit of fame for being the technology behind Bitcoin. However, beyond cryptocurrencies, it is a technology that is quite applicable to endless applications. One of the main advantages of blockchain has to do with solutions related to security, transparency, and traceability that it provides.

Introduction The last 3 years have helped us become more familiar with blockchain with cryptocurrencies rising in popularity as an investment. Although popular, blockchain is still an abstract concept and it is very common to think of it only as a speculative tool, but its applications go beyond that.

Image by Suzanne Tucker/ Shutterstock

An important pitfall to avoid when designing production-grade machine learning systems is called data leakage. Data leakage happens when a model is trained using information about the target variable that will not be available when the model is released into production. As a consequence, the reported performance of the model based on the training and validation sets will probably be very high, but it will not correspond to the performance observed in the production scenario. In some cases, the model may not be even deployable at all. There are many different contexts in which data

Agile software development requires an adaptable and flexible team willing to respond rapidly to changes, even when a client makes urgent demands while offering continuous value-driven delivery. This is what the Agile approach is all about. 

In “How Data Democratization Can Unlock Game-Changing Business Performance” we mentioned that organizations can see huge benefits from starting small and using common back-office applications such as spreadsheets to analyze data. However, starting small is not only about people, tools, and processes; it has also a lot to do with data, and it spans areas beyond only business decision-making. Small Data can also help organizations create data models without having to harvest large volumes of data to train the models.