Category: Learning Levels

In this post, we show you how to use Spark SQL in Amazon Athena notebooks and work with Iceberg, Hudi, and Delta Lake table formats. We demonstrate common operations such as creating databases and tables, inserting data into the tables, querying data, and looking at snapshots of the tables in Amazon S3 using Spark SQL in Athena.

With the launch of the neural search feature for Amazon OpenSearch Service in OpenSearch 2.9, it’s now effortless to integrate with AI/ML models to power semantic search and other use cases. OpenSearch Service has supported both lexical and vector search since the introduction of its k-nearest neighbor (k-NN) feature in 2020; however, configuring semantic search […]

In the dynamic world of cloud computing, ensuring the resilience and availability of critical applications is paramount. Disaster recovery (DR) is the process by which an organization anticipates and addresses technology-related disasters. For organizations implementing critical workload orchestration using Amazon Managed Workflows for Apache Airflow (Amazon MWAA), it is crucial to have a DR plan […]

Many organizations, small and large, are working to migrate and modernize their analytics workloads on Amazon Web Services (AWS). There are many reasons for customers to migrate to AWS, but one of the main reasons is the ability to use fully managed services rather than spending time maintaining infrastructure, patching, monitoring, backups, and more. Leadership […]

What users expect from search engines has evolved over the years. Just returning lexically relevant results quickly is no longer enough for most users. Now users seek methods that allow them to get even more relevant results through semantic understanding or even search through image visual similarities instead of textual search of metadata. Amazon OpenSearch […]

We’re living in the age of real-time data and insights, driven by low-latency data streaming applications. Today, everyone expects a personalized experience in any application, and organizations are constantly innovating to increase their speed of business operation and decision making. The volume of time-sensitive data produced is increasing rapidly, with different formats of data being […]

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. Data is stored from online systems such as the databases, CRMs, and marketing systems to data stores such as data lakes on Amazon Simple Storage Service (Amazon S3), data warehouses […]

AWS Glue is a serverless data integration service that makes it easier to discover, prepare, and combine data for analytics, machine learning (ML), and application development. You can use AWS Glue to create, run, and monitor data integration and ETL (extract, transform, and load) pipelines and catalog your assets across multiple data stores. One of […]

AWS Step Functions is a fully managed visual workflow service that enables you to build complex data processing pipelines involving a diverse set of extract, transform, and load (ETL) technologies such as AWS Glue, Amazon EMR, and Amazon Redshift. You can visually build the workflow by wiring individual data pipeline tasks and configuring payloads, retries, […]

With the exponential growth of data, companies are handling huge volumes and a wide variety of data including personally identifiable information (PII). PII is a legal term pertaining to information that can identify, contact, or locate a single person. Identifying and protecting sensitive data at scale has become increasingly complex, expensive, and time-consuming. Organizations have […]