HEMA Builds a Data Mesh to Empower Teams with Amazon DataZone

HEMA Builds a Data Mesh to Empower Teams with Amazon DataZone

Data has become a vital asset for businesses, providing essential insights to inform strategic decisions and enhance operational efficiency. However, many organizations face obstacles in leveraging their data effectively due to issues like data silos, limited discoverability, poor data quality, and a lack of data literacy and analytical capabilities. To tackle these challenges, AWS customers are turning to Amazon DataZone, a data management service designed to simplify and accelerate the cataloging, discovery, sharing, and governance of data across AWS, on-premises, and third-party sources.

HEMA, a renowned Dutch retail brand established in 1926, specializes in offering daily convenience products with a unique design ethos. With over 17,000 employees, HEMA operates more than 750 stores across the Netherlands, Belgium, Luxembourg, France, Germany, and Austria, complemented by webstores in all these regions. Since migrating its e-commerce system to AWS in 2018, HEMA has empowered its developers with the freedom to innovate using AWS Cloud tools. This transformation drives innovations like their popular online cake customization feature and democratizes data to deliver valuable business insights.

This post explores how HEMA leveraged Amazon DataZone to establish a data mesh and streamline data access across its business functions. It details HEMA’s journey to deploy Amazon DataZone, the challenges they overcame, and the significant benefits achieved since its rollout in May 2024. From creating an enterprise-wide data inventory and enhancing data discoverability to enabling decentralized data sharing and governance, Amazon DataZone has proven transformative for HEMA.

After transitioning its entire data platform to AWS Cloud, HEMA saw an opportunity to invest in building a data mesh through its Data & Cloud function.

HEMA’s enterprise architecture is uniquely service-oriented, with each service fulfilling a specific business function. Each service operates within a dedicated AWS account and is managed by a product owner and development team. Currently, HEMA operates over 400 services, with 20 dedicated to ETL pipelines that produce and consume shared data assets within the data mesh.

Challenges in Data Management

Shortly after launching its data platform, HEMA realized that its operations were not as agile or streamlined as desired. Siloed data inventories in isolated environments made data discovery and sharing a slow and manual process for teams.

Additionally, implementing robust data governance was essential. In a decentralized data mesh architecture, governance complexity increases. HEMA identified data governance as a foundational necessity for creating a reliable and efficient data organization.

Why HEMA Chose Amazon DataZone?

During the preview phase, HEMA saw that Amazon DataZone met all critical data management requirements in a unified solution. The platform offered significant advantages for both technical teams and business users:

• Technical Teams: A programmatic solution to manage the availability, accessibility, and quality of enterprise data assets.

• Business Users: A user-friendly tool to discover data assets and fulfill their data-sharing needs seamlessly.

Key features like AI-generated metadata provided reliable, use case-specific explanations of data products, while the subscription feature enabled rapid integration of data assets into user environments, replacing lengthy manual processes. These capabilities, along with its self-service features, drove HEMA’s decision to adopt Amazon DataZone at the enterprise level.

HEMA’s data ecosystem is complex, involving diverse teams using various technologies and platforms, including Databricks. To govern this multifaceted environment effectively, HEMA implemented a data mesh architecture on AWS. This architecture features a Central Intelligence Platform (CIP) that facilitates the activities of data producers and consumers, providing the necessary infrastructure and tools for efficient operations. Through this architecture, HEMA has successfully streamlined its data management processes, achieving greater agility and insight-driven decision-making.

Sanborn Head Brings Real-Time Insights to Landfill Operators with New System

Sanborn, Head & Associates Inc., a New Hampshire-based engineering and technical consulting firm, has introduced Project Portal, a new landfill data management system developed and hosted by De maximis Data Management Solutions (DDMS). The system is tailored to manage mission-critical landfill data efficiently.

Sanborn Head, known for serving private, public, and institutional clients across sectors such as development, energy, industrial, and solid waste, describes Project Portal as a "comprehensive, cloud-based environmental data management platform." It is designed to meet the specific requirements of landfill operators, providing an integrated system for making informed decisions based on accurate environmental data.

The web-based platform consolidates and processes data from various on-site landfill devices, including flow meters, flares, pump stations, and systems for wastewater, leachate treatment, and power plants. According to the company, it offers real-time data access, advanced analytics, cumulative trending, and detailed reporting. This allows landfill operators to maintain regulatory compliance while optimizing budgets. DDMS, headquartered in St. Paul, Minnesota, is a recognized leader in delivering high-quality environmental data solutions.

“Timely and accurate data are essential for landfill operators and owners,” said Mark Packard, CEO of DDMS. "We are excited to combine Sanborn Head’s extensive expertise in landfill operations with our advanced data management systems. Together, we’ll empower Sanborn Head’s clients with actionable insights, innovative tools, and high-quality data to enhance landfill management and operational performance."

“This collaboration reinforces Sanborn Head’s position as a progressive engineering consulting firm in the solid waste sector,” said Senior Vice President Brian Beaudoin, PE. "We are thrilled to offer this cutting-edge platform to our clients, as it promises to reduce costs and save time."

AI-Powered Storage Market to Redefine Data Management with Unprecedented Growth by 2033

In 2022, the AI-powered storage market was valued at $16.6 billion, growing to $21.0 billion in 2023. Over the forecast period of 2023-2033, the market is anticipated to grow at a compound annual growth rate (CAGR) of 20.7%, with revenue projected to reach approximately $138.0 billion by 2033.

The rapid expansion of the AI-powered storage market is being driven by several transformative trends in data management. Among these, the increasing adoption of hybrid systems and cloud storage stands out.

As businesses recognize the flexibility, cost-efficiency, and accessibility offered by cloud storage, they are integrating it into their data management strategies. AI technologies enable organizations to optimize cloud storage usage, automate data transfers, and ensure robust data security.

Another major growth driver is the rising demand for faster analytics and data processing. The surge in data availability has created a need for efficient, rapid analytics to extract meaningful insights. AI-powered storage systems facilitate accelerated data processing, empowering organizations to analyze data in real-time and make informed decisions. These systems leverage machine learning algorithms to identify patterns and trends within large datasets, enabling predictive analytics capabilities.

Machine learning also plays a pivotal role in enhancing storage performance and reducing costs. By analyzing data usage patterns, AI-powered storage systems can dynamically allocate resources, improve efficiency, and minimize unnecessary expenses. This ensures optimal utilization of resources and cost-effective data storage solutions.

AI-powered storage solutions are also transforming traditional storage methods. By automating data management processes, these systems reduce the need for manual intervention, streamline operations, and enhance overall data security and reliability. As AI technology continues to advance, organizations will gain increasingly sophisticated tools for managing and storing data, unlocking greater efficiency and cost savings.

These solutions also enable seamless integration of on-premises systems with cloud platforms, ensuring data is managed and stored effectively. Organizations can dynamically allocate resources, optimize performance, and eliminate superfluous expenses, resulting in a simplified and economical data management strategy.