Data governance is a complex topic. In a nutshell, it refers to the aspect of data management concerning an organization's ability to ensure (A) that high data quality exists throughout the complete data lifecycle, and (B) that sufficient data controls are in place to support business objectives. In practice, data governance is the collection of processes, roles, policies, and standards that ensure a balance between access and control for information throughout an organization.

Data has long been a critical asset for businesses like yours to understand customers, operate more efficiently, inform go-to-market strategies, and retain your best employees. In a digital world, capturing and creating data-driven insights provides a major competitive advantage for those who can turn insights into action.

In part one and two, we introduced Iguazio's feature store and discussed the benefits of using one in the ML workflow. Additionally, we ingested and transformed the data that we will be using to train our model. In this blog, we will do the following.

This short post by a member of Ably's engineering team describes how we resolved a problem that is typical of the challenges we face each week. We thrive on solving hard distributed system problems that are mostly platform agnostic and theoretical in nature, and this is the first post in a long-term series of articles about things we've learned recently.

When trying to find the perfect database to store your company’s valuable information and data, there are many elements to consider. And, while there are a number of great databases available for companies to choose from, the process of choosing the right database for your company’s needs and goals can still be a difficult process. However, as you weigh your options, one database that needs to be on your list of considerations is Vertica.

The API economy is growing rapidly. According to research by Coleman Parkes enterprises were twice as likely as their peers to be confident they are differentiating themselves by using Application Programming Interfaces. The same report showed that companies with advanced API management processes experience up to 47 percent better business results than those with basic API management.

A native library is a library containing code compiled for a specific (native) architecture. There are certain scenarios like hardware-software integrations and process optimizations where using libraries written for different platforms can be very useful or even necessary.

Threads are a basic concept in concurrent and parallel programming . They allow programs to do multiple things at the same time and are often used for performing computationally intensive tasks in the background without interrupting the main program. This is accomplished through multithreading, a common programming and execution model which allows multiple threads to exist within the context of one process. These threads share resources but are able to execute independently.

Organizations increasingly turn to AI to transform work processes, but this rapid adoption of models has amplified the need for explainable AI. Explaining AI helps us understand how and why models make predictions. For example, a financial institution might wish to use an AI model to automatically flag credit card transactions for fraudulent activity. While an accurate fraud model would be a first step, accuracy alone isn’t sufficient.

Test Automation is a necessary precondition for high-quality modern development. Testing and test automation must be integrated into the software delivery processes to give the team the right level of feedback, at the right time, and to ensure high-quality software. One of the biggest challenges of building a test automation framework that works on a long-term, scalable basis, is that it requires fundamentally different conditions compared to a predominantly manual testing approach.