Category: AWS Lambda

You can build data lakes with millions of objects on Amazon Simple Storage Service (Amazon S3) and use AWS native analytics and machine learning (ML) services to process, analyze, and extract business insights. You can use a combination of our purpose-built databases and analytics services like Amazon EMR, Amazon OpenSearch Service, and Amazon Redshift as […]

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Search engines provide the means to retrieve relevant content from a collection of content. However, this can be challenging if certain exact words aren’t entered. You need to find the right item from a catalog of products, or the correct […]

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Let’s describe the typical use case where a tracking pixel solution, also known as a web beacon, might help you: Analyzing web traffic is critical to understanding […]

A common challenge ETL and big data developers face is working with data files that don’t have proper name header records. They’re tasked with renaming the columns of the data files appropriately so that downstream application and mappings for data load can work seamlessly. One example use case is while working with ORC files and […]

In Part 1 of this two-part post, we looked at how we can create an AWS Glue ETL job that is agnostic enough to rename columns of a data file by mapping to column names of another file. The solution focused on using a single file that was populated in the AWS Glue Data Catalog […]

Part 1 of this series explains the importance of building and implementing a customer experience (CX) management and data monetization strategy for telecom service providers (TSPs), and the major challenges driving these initiatives. It also includes an AWS CloudFormation template to set up a demonstration of the solution using AWS services. It covers transforming and enriching […]

Proper data management is critical to successful, data-driven decision-making. An increasingly large number of customers are adopting data lakes to realize deeper insights from big data. As part of this, you need clean and trusted data in order to gain insights that lead to improvements in your business. As the saying goes, garbage in is […]

November 2024: This post was reviewed and updated for accuracy. Many organizations are processing and analyzing clickstream data in real time from customer-facing applications to look for new business opportunities and identify security incidents in real time. A common practice is to consolidate and enrich logs from applications and servers in real time to proactively […]

The success of many modern streaming applications depends on the ability to sequentially detect each change as soon as possible after it occurs, while continuing to monitor the data stream as it evolves. Applications of change point detection range across genomics, marketing, and finance, to name a few. In genomics, change point detection can help […]

Event–driven applications are becoming popular with many customers, where applications run in response to events. A primary benefit of this architecture is the decoupling of producer and consumer processes, allowing greater flexibility in application design and building decoupled processes. An example of an even-driven application is an automated workflow being triggered by an event, which […]