Category: Analytics

Welcome to the third post of a multi-part series that addresses disaster recovery (DR) strategies with the use of AWS-managed services to align with customer requirements of performance, cost, and compliance. In part two of this series, we introduced a DR concept that utilizes managed services through a backup and restore strategy with multiple Regions. […]

Data proliferation has become a norm and as organizations become more data driven, automating data pipelines that enable data ingestion, curation, and processing is vital. Since many organizations have thousands of time-bound, automated, complex pipelines, monitoring their telemetry information is critical. Keeping track of telemetry data helps businesses monitor and recover their pipelines faster which results […]

April, 2026: Aurora Serverless v2 has been renamed Aurora serverless. No action required. In this blog post, we show you how to build an event-driven and serverless solution for property leasing and search that is scalable and resilient. This solution was created for AvalonBay Communities, Inc.—a leading residential Real Estate Investment Trusts (REITs). It enables: […]

Text data is a common type of unstructured data found in analytics. It is often stored without a predefined format and can be hard to obtain and process. For example, web pages contain text data that data analysts collect through web scraping and pre-process using lowercasing, stemming, and lemmatization. After pre-processing, the cleaned text is […]

Healthcare data is being generated at an increased rate with the proliferation of connected medical devices and clinical systems. Some examples of these data are time-sensitive patient information, including results of laboratory tests, pathology reports, X-rays, digital imaging, and medical devices to monitor a patient’s vital signs, such as blood pressure, heart rate, and temperature. […]

The deprecation of digital consumer identifiers, such as third-party cookies and mobile advertising IDs, and the rapid growth of data from expanding consumer touchpoints, has created challenges in identifying, managing, and reaching customers in digital channels. Organizations must rethink their strategies for collecting and storing customer data. Customer Data Platforms (CDPs) collect, aggregate, and organize […]

In the first part of this blog series, Optimize your modern data architecture for sustainability: Part 1 – data ingestion and data lake, we focused on the 1) data ingestion, and 2) data lake pillars of the modern data architecture. In this blog post, we will provide guidance and best practices to optimize the components […]

The Internet of Things (IoT) brings sensors, cloud computing, analytics, and people together to improve productivity and efficiency. It empowers customers with the intelligence they need to build new services and business models, improve products and services over time, understand their customers’ needs to provide better services, and improve customer experiences. Business operations become more […]

The modern data architecture on AWS focuses on integrating a data lake and purpose-built data services to efficiently build analytics workloads, which provide speed and agility at scale. Using the right service for the right purpose not only provides performance gains, but facilitates the right utilization of resources. Review Modern Data Analytics Reference Architecture on […]

Shiji Group provides global software solutions for the hospitality industry. The Shiji Enterprise Platform enables customers to manage large hotel property portfolios using software as a service (SaaS). Among functionalities such as reservations, housekeeping, finance, and integrations with external systems, the guest profile is a key aspect of the system. Besides personal information (such as […]