CIO
DECEMBER 20, 2024
Data architecture definition Data architecture describes the structure of an organizations logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF). An organizations data architecture is the purview of data architects. Ensure security and access controls.
CIO
NOVEMBER 27, 2024
To succeed, Operational AI requires a modern data architecture. These advanced architectures offer the flexibility and visibility needed to simplify data access across the organization, break down silos, and make data more understandable and actionable.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
CIO
NOVEMBER 19, 2024
While that is true, your development teams may not be ready to implement yet. Development teams starting small and building up, learning, testing and figuring out the realities from the hype will be the ones to succeed. Therefore, the developers/testers that use that code need to make sure they understand the code that is generated.
Martin Fowler
JUNE 13, 2023
Matthew Foster describes an example of this from his work with clients, and how using Domain-Driven Design and Team Topologies helped create a modular architecture that substantially reduced the time needed to deliver new features.
Speaker: Jeremiah Morrow, Nicolò Bidotti, and Achille Barbieri
In this webinar, learn how Enel Group worked with Agile Lab to implement Dremio as a data mesh solution for providing broad access to a unified view of their data, and how they use that architecture to enable a multitude of use cases.
CIO
OCTOBER 30, 2024
To overcome those challenges and successfully scale AI enterprise-wide, organizations must create a modern data architecture leveraging a mix of technologies, capabilities, and approaches including data lakehouses, data fabric, and data mesh. Another challenge here stems from the existing architecture within these organizations.
Xebia
DECEMBER 16, 2024
The rise of platform engineering Over the years, the process of software development has changed a lot. Initially, our industry relied on monolithic architectures, where the entire application was a single, simple, cohesive unit. DevOps The introduction of DevOps marked a cultural and operational shift in software development.
Advertisement
Apache Cassandra is an open-source distributed database that boasts an architecture that delivers high scalability, near 100% availability, and powerful read-and-write performance required for many data-heavy use cases.
Speaker: Leo Zhadanovsky, Principal Solutions Architect, Amazon Web Services
Amazon's journey to its current modern architecture and processes provides insights for all software development leaders. The result was enabling developers to rapidly release and iterate software while maintaining industry-leading standards on security, reliability, and performance.
Advertiser: Datadog
The premise of SLIs/SLOs is that all teams—product, architecture, development, and platform— need to look at services from the customer’s perspective. Service Level Indicators and Service Level Objectives are now the principal tools for focusing on what really matters.
Speaker: Dr. Rebecca Parsons, CTO of ThoughtWorks
The software development ecosystem exists in a state of dynamic equilibrium, where any new tool, framework, or technique leads to disruption and the establishment of a new equilibrium. It’s no surprise many CIOs and CTOs are struggling to adapt, in part because their architecture isn’t equipped to evolve.
Advertisement
To address this, a next-gen cloud data lake architecture has emerged that brings together the best attributes of the data warehouse and the data lake. This new open data architecture is built to maximize data access with minimal data movement and no data copies.
Advertisement
That’s why we developed this white paper to give you insights into four key open-source technologies – Apache Cassandra®, Apache Kafka®, Apache Spark™, and OpenSearch® – and how to leverage them for lasting success.
Advertiser: Datadog
Particularly well-suited for microservice-oriented architectures and agile workflows, containers help organizations improve developer efficiency, feature velocity, and optimization of resources. Containers power many of the applications we use every day.
Advertiser: Data Robot
As enterprises evolve their AI from pilot programs to an integral part of their tech strategy, the scope of AI expands from core data science teams to business, software development, enterprise architecture, and IT ops teams.
Expert insights. Personalized for you.
183 
Let's personalize your content