Data cleansing is a fundamental aspect of knowing what data you retain and using it most effectively. The process of cleansing reduces the potential for error and enhances data reliability. Here's how to get started.

In the first of this two-part episode of Data+AI Battlescars, Sandeep Uttamchandani, Unravel Data’s CDO, speaks with Kapil Surlaker, VP of Engineering and Head of Data at LinkedIn. In this first part, they cover LinkedIn’s challenges related to Metadata Management and Data Access APIs. Part 2 will dive deep into data quality.

Build a comprehensive picture of how customers interact with your company.

We’re all familiar with how Google Search revolutionized information processing for consumers. The ingenious combination of AI with a new way to organize content on the web created a user-friendly experience that forever changed how the world finds relevant information on the internet.

During your Android developer career, you may reach a point where you will have to develop Android libraries or Gradle plugins. In this article, we will discuss the most important aspects and differences of testing these!

The pandemic upended business for many or at the very least cast a grim shade of uncertainty, so, as many took to working from home, they also were commissioned with cutting waste. Among the biggest sources of misspend in 2020 – cloud services. And remote work may have actually spurred the problem, as organizations migrate more applications to the cloud to support these workers.

For our latest specialist interview in our series speaking to technology leaders from around the world, we’ve welcomed the COO of DNSFilter, Jen Ayers to share her insights from the world of cybersecurity including the latest trends she is seeing on the rise and what business leaders need to keep in mind for the rest of 2021.

News of the latest massive data breach is always in the headlines. How can you avoid being next on the list? In order to function, businesses of all sizes and industries need to collect personally identifiable information (PII) about their employees and customers—but they also need to take proactive steps to keep this information secure and defend against PII breaches. PII substitution is an effective tactic to shield your sensitive and confidential data from prying eyes.

In this episode of Data+AI Battlescars (formerly CDO Battlescars), Sandeep Uttamchandani talks to Chu-Cheng, CDO at Etsy. This episode focuses on Chu-Cheng’s battlescars related to recruiting and building a data science team. Chu-Cheng leads the global data organization at Etsy. He’s responsible for data science, AI innovation, machine learning and data infrastructure. Prior to Etsy, Chu-Cheng has led various data roles, including at Amazon, Intuit, Rakuten and eBay.

Many software companies have no formal quality assurance strategy, and those that do take one of two inherently flawed approaches: Either they (a) ask developers to do QA or (b) delegate QA to a siloed team, whether it’s internal or outsourced. Having been in the QA space for a decade, we’ve learned that both approaches are deeply flawed.