Category: Analytics

This post was co-written by Rajat Bhardwaj, Senior Technical Account Manager at AWS and Kunal Upadhyay, General Manager at Paytm. Paytm is India’s leading payment platform, pioneering the digital payment era in India with 130 million active users. Paytm operates multiple lines of business, including banking, digital payments, bill recharges, e-wallet, stocks, insurance, lending and […]

Email is one of the most important methods for business communication across many organizations. It’s also one of the primary methods for many businesses to communicate with their customers. With the ever-increasing necessity to send emails at scale, monitoring and analysis has become a major challenge. Amazon Simple Email Service (Amazon SES) is a cost-effective, […]

With real-time information about customers, products, and applications in hand, organizations can take action as events happen in their business application. For example, you can prevent financial fraud, deliver personalized offers, and identify and prevent failures before they occur in near real time. Although batch analytics provides abilities to analyze trends and process data at […]

Many organizations prefer SQL for data preparation because they already have developers for extract, transform, and load (ETL) jobs and analysts preparing data for machine learning (ML) who understand and write SQL queries. Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (Amazon S3) using […]

This is a guest blog post co-written by Tal Knopf at Coralogix. Digital data is expanding exponentially, and the existing limitations to store and analyze it are constantly being challenged and overcome. According to Moore’s Law, digital storage becomes larger, cheaper, and faster with each successive year. The advent of cloud databases is just one […]

Amazon QuickSight is a serverless, cloud-based business intelligence (BI) service that brings data insights to your teams and end users through machine learning (ML) powered dashboards and data visualizations, which can be access via QuickSight or embedded in apps and portals that your users access. This post shares the top QuickSight features and updates launched […]

Amazon EMR is a cloud big data platform for running large-scale distributed data processing jobs, interactive SQL queries, and machine learning (ML) applications using open-source analytics frameworks such as Apache Spark, Apache Hive, and Presto. Amazon EMR supports Kerberos for authentication; you can enable Kerberos on Amazon EMR and put the cluster in a private […]

Data lakes use a ring of purpose-built data services around a central data lake. Data needs to move between these services and data stores easily and securely. The following are some examples of such services: Amazon Simple Storage Service (Amazon S3), which stores structured, unstructured, and semi-structured data Amazon Redshift, a fully managed, petabyte-scale data […]

November 2022: This post was updated to accommodate changes introduced by Amazon Redshift Streaming Ingestion becoming Generally Available. Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL. Amazon Redshift offers up to three times better price performance […]

Amazon EMR on Amazon EKS is a deployment option offered by Amazon EMR that enables you to run Apache Spark applications on Amazon Elastic Kubernetes Service (Amazon EKS) in a cost-effective manner. It uses the EMR runtime for Apache Spark to increase performance so that your jobs run faster and cost less. In our benchmark […]