Showing posts from November, 2021

The Data Mesh - should you adapt?

In actuality, not every firm may be a good fit for the implementation of a Data Mesh.  Larger enterprises that experience uncertainty and change in their operations and environment are the primary target audience for Data Mesh.  A Data Mesh is definitely an unnecessary expense if your organization's data requirements are modest and remain constant over time. What is a "Data Mesh"? As it focuses on delivering useful and safe data products, Data Mesh is a strategic approach to modern data management and a strategy to support an organization's journey toward digital transformation. Data Mesh's major goal is to advance beyond the established centralized data management techniques of using data warehouses and data lakes. By giving data producers and data consumers the ability to access and handle data without having to go through the hassle of involving the data lake or data warehouse team, Data Mesh highlights the concept of organizational agility. Data Mesh's dec

Federated Learning: Old Wine in a New Bottle?

Machine Learning (ML) is a specific subset (branch) of Artificial Intelligence (AI). The main idea of ML is to enable systems to learn from historical data to predict new output values for input events. The beauty is that ML does not require systems to be explicitly programmed to achieve so. All this with little human intervention. With the growing volumes of data in today’s world, ML has gained unprecedented popularity. We can achieve today what it was unimaginable yesterday: from predicting cancer risk from mammogram to polyglot AI translators. As a result, ML has become the key competitive differentiator for many companies, leading ML-powered software to quickly become omnipresent in our lives. The key in ML is that the more available data the better the accuracy of the predictive models. The Appearance of Distributed ML While ML has become a quite powerful technology, its hunger for training data makes it hard to build ML models in a single machine. It is not unusual to see trainin