This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Key Takeaways: Data mesh is a decentralized approach to datamanagement, designed to shift creation and ownership of data products to domain-specific teams. Data fabric is a unified approach to datamanagement, creating a consistent way to manage, access, and share data across distributed environments.
Whether it’s unifying transactional and analytical data with Hybrid Tables, improving governance for an open lakehouse with Snowflake Open Catalog or enhancing threat detection and monitoring with Snowflake Horizon Catalog , Snowflake is reducing the number of moving parts to give customers a fully managed service that just works.
In August, we wrote about how in a future where distributed dataarchitectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI.
Open data is the future. And for that future to be a reality, data teams must shift their attention to metadata, the new turf war for data. The need for unified metadata While open and distributed architectures offer many benefits, they come with their own set of challenges. Unifying the data isn’t enough.
To improve the way they model and manage risk, institutions must modernize their datamanagement and data governance practices. Up your liquidity risk management game Historically, technological limitations made it difficult for financial institutions to accurately forecast and manage liquidity risk.
In this episode Kevin Liu shares some of the interesting features that they have built by combining those technologies, as well as the challenges that they face in supporting the myriad workloads that are thrown at this layer of their data platform. Can you describe what role Trino and Iceberg play in Stripe's dataarchitecture?
Agencies are plagued by a wide range of data formats and storage environments—legacy systems, databases, on-premises applications, citizen access portals, innumerable sensors and devices, and more—that all contribute to a siloed ecosystem and the datamanagement challenge. . Modern dataarchitectures.
Monitor and Adapt: Continuously assess the impact of GenAI on data governance practices and be prepared to adapt policies as technologies evolve. Data governance is the only way to ensure those requirements are met. Chief Technology Officer, Finance Industry For all the quotes, download the Trendbook today!
In this episode Satish Jayanthi explores the benefits of incorporating column-aware tooling in the data modeling process. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement RudderStack helps you build a customer data platform on your warehouse or data lake.
At Precisely’s Trust ’23 conference, Chief Operating Officer Eric Yau hosted an expert panel discussion on modern dataarchitectures. The group kicked off the session by exchanging ideas about what it means to have a modern dataarchitecture.
Track data files within the table along with their column statistics. Open table formats enable efficient datamanagement and retrieval by storing these files chronologically, with a history of DDL and DML actions and an index of data file locations. Log all Inserts, Updates, and Deletes (DML) applied to the table.
Enter data fabric: a datamanagementarchitecture designed to serve the needs of the business, not just those of data engineers. A data fabric is an architecture and associated data products that provide consistent capabilities across a variety of endpoints spanning multiple cloud environments.
Enter data fabric: a datamanagementarchitecture designed to serve the needs of the business, not just those of data engineers. A data fabric is an architecture and associated data products that provide consistent capabilities across a variety of endpoints spanning multiple cloud environments.
Key Takeaways Data Fabric is a modern dataarchitecture that facilitates seamless data access, sharing, and management across an organization. Datamanagement recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata.
Companies can now capitalize on the value in all their data, by delivering a hybrid data platform for modern dataarchitectures with data anywhere. Cloudera Data Platform (CDP) is designed to address the critical requirements for modern dataarchitectures today and tomorrow.
The concept of the data mesh architecture is not entirely new; Its conceptual origins are rooted in the microservices architecture, its design principles (i.e., need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g., Components of a Data Mesh.
She also discusses her views on the role of the data lakehouse as a building block for these architectures and the ongoing influence that it will have as the technology matures. Atlan is the metadata hub for your data ecosystem. And don’t forget to thank them for their continued support of this show!
He also explains which layers are useful for the different members of the business, and which pitfalls to look out for along the path to a mature and flexible data platform. How do you define data curation? How does the size and maturity of a company affect the ways that they architect and interact with their data systems?
In fact, we recently announced the integration with our cloud ecosystem bringing the benefits of Iceberg to enterprises as they make their journey to the public cloud, and as they adopt more converged architectures like the Lakehouse. 1: Multi-function analytics . 3: Open Performance.
Over the years, the technology landscape for datamanagement has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. Each of these architectures has its own unique strengths and tradeoffs.
To name a few: privacy and security considerations compliance demands interest in emerging datamanagementarchitectures like data mesh and data fabric increased AI adoption The findings show that data governance is the most-cited data challenge inhibiting progress toward AI initiatives (62%).
To get a better understanding of a data architect’s role, let’s clear up what dataarchitecture is. Dataarchitecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. Sample of a high-level dataarchitecture blueprint for Azure BI programs.
Rather than manually defining all of the mappings ahead of time, we can rely on the power of graph databases and some strategic metadata to allow connections to occur as the data becomes available. If you are struggling to maintain a tangle of data pipelines then you might find some new ideas for reducing your workload.
Announcements Welcome to the Data Engineering Podcast, the show about modern datamanagement When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.
With Cloudera’s vision of hybrid data , enterprises adopting an open data lakehouse can easily get application interoperability and portability to and from on premises environments and any public cloud without worrying about data scaling. Why integrate Apache Iceberg with Cloudera Data Platform?
In this episode he explains his motivation for creating a product for datamanagement, how the programming model simplifies the work of building testable and maintainable pipelines, and his vision for the future of data programming. If you are building dataflows then Dagster is definitely worth exploring.
Dataform is a platform that helps you apply engineering principles to your data transformations and table definitions, including unit testing SQL scripts, defining repeatable pipelines, and adding metadata to your warehouse to improve your team’s communication. What do you have planned for the future of DataForm?
Different data types need different types of analytics – real-time, streaming, operational, data warehouses. As Mason said, all the datamanagement, data analytics, and data science tools should easily work together and run against all this shared data. It should run on any cloud or on-prem.
Not too long ago, almost all dataarchitectures and data team structures followed a centralized approach. As a data or analytics engineer, you knew where to find all the transformation logic and models because they were all in the same codebase. Your organization may be undergoing the decentralization of data.
Capital One: Insights on building a data strategy to drive business value One of the hotly debated and many companies struggling with is to build an agile data strategy to drive business value. There is no shortage of data, but datamanagement is still hard, which requires skillful execution and alignment across the org.
Data by itself has no value, it needs to be organized, standardized, and clean. In this context, datamanagement in an organization is a key point for the success of its projects involving data. One of the main aspects of correct datamanagement is the definition of a dataarchitecture.
While Cloudera CDH was already a success story at HBL, in 2022, HBL identified the need to move its customer data centre environment from Cloudera’s CDH to Cloudera Data Platform (CDP) Private Cloud to accommodate growing volumes of data. See other customers’ success here .
As organizations seek greater value from their data, dataarchitectures are evolving to meet the demand — and table formats are no exception. At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files.
Data Catalog as a passive web portal to display metadata requires significant rethinking to adopt modern data workflow, not just adding “modern” in its prefix. I know that is an expensive statement to make😊 To be fair, I’m a big fan of data catalogs, or metadatamanagement , to be precise.
This capability is useful for businesses, as it provides a clear and comprehensive view of their data’s history and transformations. Data lineage tools are not a new concept. In this article: Why Are Data Lineage Tools Important? It provides context for data, making it easier to understand and manage.
In this post, I’ll explore the origins of the modern data stack, discuss why its promised benefits have proven elusive, and advocate for a post-modern approach to datamanagement that prioritizes productivity and value. Where did the modern data stack come from?
Cloudera’s data superheroes design modern dataarchitectures that work across hybrid and multi-cloud and solve complex datamanagement and analytic use cases spanning from the Edge to AI. DATA SECURITY AND GOVERNANCE.
Well, there’s a new phenomenon in datamanagement that received the name of a data lakehouse. The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. Data warehouse.
DataOps Architecture: 5 Key Components and How to Get Started Ryan Yackel August 30, 2023 What Is DataOps Architecture? DataOps is a collaborative approach to datamanagement that combines the agility of DevOps with the power of data analytics. As a result, they can be slow, inefficient, and prone to errors.
Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. 2023 predictions from the panel are; Unified metadata becomes kingmaker.
Summit Essentials Date & Location The Gartner Data & AI Summit takes place May 12-15th, 2025 in London, England. This year, the event will uncover the latest in datamanagement, data trends, governance, and dataarchitecture to deliver value for the future.
That’s why we’re excited to announce that uniting diverse data team personas to collectively ensure data quality just got easier, thanks to a new integration between Monte Carlo’s data observability platform and Atlan’s active metadata platform.
In the past year, businesses who doubled down on digital transformation during the pandemic saw their efforts coming to fruition in the form of cost savings and more streamlined datamanagement. These features provide businesses with a common metadata, security, and governance model across all their data.
We organize all of the trending information in your field so you don't have to. Join 37,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content