AWS Big Data Blog

This is a guest post by Miguel Chin, Data Engineering Manager at OLX Group and David Greenshtein, Specialist Solutions Architect for Analytics, AWS. OLX Group is one of the world’s fastest-growing networks of online marketplaces, operating in over 30 countries around the world. We help people buy and sell cars, find housing, get jobs, buy […]

This post was co-written with Amit Shah, Principal Consultant at Atos. Customers across industries seek meaningful insights from the data captured in their Customer Relationship Management (CRM) systems. To achieve this, they combine their CRM data with a wealth of information already available in their data warehouse, enterprise systems, or other software as a service […]

It’s common to ingest multiple data sources into Amazon Redshift to perform analytics. Often, each data source will have its own processes of creating and maintaining data, which can lead to data quality challenges within and across sources. One challenge you may face when performing analytics is the presence of imperfect duplicate records within the source data. This post presents one possible approach to addressing this challenge in an Amazon Redshift data warehouse using fuzzy matching.

This is a guest post by Siva Manickam and Prahalathan M from Vyaire Medical Inc. Vyaire Medical Inc. is a global company, headquartered in suburban Chicago, focused exclusively on supporting breathing through every stage of life. Established from legacy brands with a 65-year history of pioneering breathing technology, the company’s portfolio of integrated solutions is […]

In the data analytics space, organizations often deal with many tables in different databases and file formats to hold data for different business functions. Business needs often drive table structure, such as schema evolution (the addition of new columns, removal of existing columns, update of column names, and so on) for some of these tables […]

In the post Introducing the AWS ProServe Hadoop Migration Delivery Kit TCO tool, we introduced the AWS ProServe Hadoop Migration Delivery Kit (HMDK) TCO tool and the benefits of migrating on-premises Hadoop workloads to Amazon EMR. In this post, we dive deep into the tool, walking through all steps from log ingestion, transformation, visualization, and […]

When migrating Hadoop workloads to Amazon EMR, it’s often difficult to identify the optimal cluster configuration without analyzing existing workloads by hand. To solve this, we’re introducing the Hadoop migration assessment Total Cost of Ownership (TCO) tool. You now have a Hadoop migration assessment TCO tool within the AWS ProServe Hadoop Migration Delivery Kit (HMDK). […]

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that makes it simple to set up and operate end-to-end data pipelines in the cloud at scale. A data pipeline is a set of tasks and processes used to automate the movement and transformation of data between different systems.­ […]

For data lake customers who need to discover petabytes of data, AWS Glue crawlers are a popular way to discover and catalog data in the background. This allows users to search and find relevant data from multiple data sources. Many customers also have data in managed operational databases such as MongoDB Atlas and need to […]

Since its launch in 2006, Amazon Simple Storage Service (Amazon S3) has experienced major growth, supporting multiple use cases such as hosting websites, creating data lakes, serving as object storage for consumer applications, storing logs, and archiving data. As the application portfolio grows, customers tend to store data from multiple application and different business functions […]