Systems | Development | Analytics | API | Testing

When I was working at Google back in the mid 2000’s, we dealt with tens of billions of ad impressions a day, trained several machine learning models on years worth of historic data, and used frequently-updated models in ranking ads. The whole system was an amazing feat of engineering and there was no system out there that was even close to handling this much data. It took us years and hundreds of engineers to make this happen, today, the same scale can be achieved in any enterprise.

When we talk about technology, we should try to do it in the simplest possible terms. But while we hear many CEOs and other tech executives preach this advice, it’s rarely followed—and the workflow software space is no exception. Popular workflow lingo like hyperautomation, digital process automation, and intelligent automation all mean essentially the same thing: to digitize processes for efficiency, consistency, and compliance.

Better HR analytics bring benefits to every business, but data integration must come first.

Welcome to the second installment of our ChaosSearch for FinTech blog series, where we explore how financial technology (FinTech) companies can solve analytics challenges and drive business outcomes with ChaosSearch. In Part One of this series, we brought you an in-depth look at how FinTech companies could accelerate application development and streamline operations in the cloud by adopting ChaosSearch for log analytics at scale.

These days, thanks to the Internet, any person or business can become a brand. Yet, not many of those brands manage to become known or recognizable. Building brand awareness takes a lot of time and effort, and it all starts with creating a consistent visual identity.

Visualize and share the insights that matter from your Excel data, now powered by Databox.

Flask and Django are two of the most popular Python packages. More importantly, they are the two most preferred web frameworks you can use with the language. Both frameworks are open-source and offer excellent APIs for developers to build robust Python web applications. While both frameworks serve the same purpose, they take two philosophically opposed routes to achieve it.

Today, we are excited to announce the public preview of search indexes and related SQL SEARCH functions in BigQuery. This is a new capability in BigQuery that allows you to use standard BigQuery SQL to easily find unique data elements buried in unstructured text and semi-structured JSON, without having to know the table schemas in advance. By making row lookups in BigQuery efficient, you now have a powerful columnar store and text search in a single data platform.

In the latest instalment of our interviews speaking to leaders throughout the world of tech, we’ve welcomed Chris Duffey, who leads Strategic Development at Adobe. Chris spearheads Adobe's Creative Cloud strategic development partnerships across the Creative enterprise space and has been profiled by The Wall Street Journal, The Guardian, Inc., Adweek, Adage, Cheddar, The Mirror, The Drum, Campaign and CMO.com.

Object-oriented programming (OOP) is hard to achieve in a dynamic prototypical language like JavaScript. You have to manually stick to OOP principles because of language features like duck typing. This requires discipline, as nothing in the language enforces the principles. If a diverse team of developers with different backgrounds is involved, a codebase filled with good intentions can quickly become one chaotic mess.