When talking about data analysis, Pandas is surely the most powerful and widely used Python library for data manipulation, cleaning, and preprocessing. Thanks to its features, in fact, we can work with tabular data, retrieving them from SQL … Read more
Data Analysis
Logical Data Warehouses vs. Traditional Data Warehouses
Data warehouses play a crucial role in today's data-intensive operations. However, the physical infrastructures required for Big Data are increasingly being jettisoned in favour of more agile solutions. Logical data warehouses add a virtual … Read more
Data-Centric AI: The Key to Unlocking the Full Potential of Machine Learning
I. Introduction: data-centric vs model-centric AI The potential of machine learning is yet to be fully explored, even though it has already revolutionized the way we process and analyze data. That's where data-centric AI comes in. By … Read more
Black Friday: How to Manage Huge Traffic on Your App
It's a known issue both for users and developers: the extra traffic during Black Friday and Cyber Monday can cause e-commerce and payment apps to crash, generating many problems such as bad user experience, faulty transactions, revenue loss due to … Read more
Working with Date Intervals in Data Warehouses and Data Lakes
Working as Data Engineer makes you work with dates and time data a lot. Especially in the recent period where companies want to be Data-Driven, the software is Event-driven, your coffee machine is data-driven, and AI and ML require tons of data to … Read more
Take Data to the Next Level With Graph Machine Learning
This guide explores Graph Machine Learning (also known as Graph ML), the science that combines graph theory with ML. Let's start with the basics: A graph can be defined as a collection of nodes and their relationships. An example would be two … Read more
Everything You Need to Know on How to Test AI-Driven Systems
Whichever way you look, tech influences every aspect of our lives, and at the heart of this digitization is Artificial Intelligence (AI). With proper integration, AI systems can power many aspects of your business. An example is that, for a long … Read more
How Data Observability Can Boost IT Performance in the Banking Sector
Many industries have found themselves having to move quickly to keep up with changing technologies, and the world of fintech has felt this change more than most. Few consumer services command the desire for security that financial institutions such … Read more
Ruby on Rails in 2022? A Data Processing and Visualization Case Study
This article, developed together with Mònade, shares insight about data science and dives deep into the usage of Ruby on Rails for data visualization and processing through a practical example: Adalytics. Data is everywhere, from the billions of … Read more
What is Synthetic Monitoring and 5 Reasons Your Business Needs It
At its core, synthetic monitoring is the practice of using an automated script to emulate the role of a customer or user. Think of it this way. Imagine you run a small online call center. You want to find the best headset for conference … Read more
Red Team vs Blue Team Exercise: Its Role in Finding Your Cybersecurity Flaws
What Is the Red Team Vs Blue Team Exercise? The red team vs blue exercise is an industry-standard exercise for testing security processes. It originated from a military ‘wargames’ model. The strategy pits the teams against each other in … Read more
How Can AI support Football Tech Staff in Technical and Tactical Analysis and Decision Making?
Introduction Currently, science and technology are data-driven, as most business activities are (or should be) and sport is no exception: indeed, one can collect huge amounts of data from a team sports match, such as a basketball, volleyball or … Read more
Responsible Production and Green Consumption: How to Find a Sustainable Path forward and Avoid Waste
Current approaches to water, food, and production need to be reverse-engineered worldwide to achieve real sustainability for the global population. ICT technology provides the foundation on which to build disruptive solutions that will change the … Read more
Population Shift Analysis: Monitoring Data Quality with Popmon
One of the most significant parts of any data-driven application is data quality assessment. Before you start using your data, you must understand how good - or bad - it is. This is why data analysis and data cleaning activities are performed - … Read more
How Augmented Reality (AR) Enables Remote Troubleshooting
Thinking about a production chain within big industry, it is easy to imagine how many machines must work together to provide high productivity levels. In such contexts, a single faulty mechanism can have a huge impact on the whole chain, causing … Read more
Watson Studio: IBM Extends Open Source to the Production Phase to All Stakeholders
Is Open Source ideal for AI use in business? By the time you leave university, you will already be using many tools and platforms from the open-source environment. Open Source offers an infinite number of tools, essentially free of cost. … Read more
8 Techniques for Efficient Data Cleaning
Data is an essential part of data analytics, data security, and data science. That’s obvious. Sometimes, however, that data can get a little dirty. No, not like in a gangster film. More like where suddenly we are having to deal with ‘dirty data’ … Read more
7 Key Differences Between Data Analytics and Data Mining
With every second we spend online, mountains of data is generated. For every social media post, Google search, and link clicked, there is a way in which our activity can be collected for data. Experts within the data science field can utilize this, … Read more
5 Rules of Engagement When it Comes to Data Visualization
So you’ve been out, you’ve conducted the surveys, you’ve collected a giant pot of data that unequivocally demonstrates your position and now it’s time to present. How do you do it? Well you could just dump the raw spreadsheet at the desk of your … Read more
What Are the Main Areas of Development for a Data Analyst’s Career?
Data analysts manipulate data and use it to help organisations make wise business decisions. They gather information from the data regarding specific aspects, interpret, analyse and share their findings with other stakeholders in the organisation … Read more