Many enterprises face significant challenges when it comes to building data pipelines in AWS, particularly around data ingestion. As data from diverse sources continues to grow exponentially, managing and processing it efficiently in AWS is critical. Without these capabilities, it’s harder to analyze and get any meaning from your data.

Learn about an architecture built on BigQuery Omni that reduces the overall cost of log analytics by 10x as compared to a traditional approach.

For iPhone and iPad app development, one of the main aspects is the app’s performance. Performance is about your application not crashing, but also how quickly and smoothly it can carry out its functions when users interact with it. An application whose functions consume a lot of battery life, or an application that doesn’t like to wait too long until it finishes whatever it wants to do, can lead to users uninstalling the app.

BigQuery’s pipe syntax introduces an intuitive, top-down syntax for understanding data transformations, and is used in Cloud Logging Log Analytics.

Kotlin Generics are a way to use generics in Kotlin that have type parameters specified to their usage. This powerful tool defines code components so that they will work with any data type in a flexible and reusable manner – and the main advantage of Kotlin Generics is how they are statically-typed.

While data lakes make it easy to store and analyze a wide variety of data types, they can become data swamps without the proper documentation and governance. Until you solve the biggest data lake challenges — tackling exponential big data growth, costs, and management complexity — efficient and reliable data analytics will remain out of reach.

Databricks is lighting the way for organizations to thrive in an increasingly AI-driven world. The Databricks Platform is built on lakehouse architecture, empowering organizations to break down existing data silos, store enterprise data in a single centralized repository with unified data governance powered by Unity Catalog, and make the data available to a variety of user groups to support diverse analytics use cases.

Logging plays a crucial role in app development. As well as debugging everyday issues with the product, a good logger will monitor application behavior and gain insights into user interactions. This is particularly crucial for iOS developers given the frequency of Apple’s official updates and the ferocious competition in the marketplace.