AltexSoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Cloudera

JUNE 7, 2022

Companies can now capitalize on the value in all their data, by delivering a hybrid data platform for modern data architectures with data anywhere. Cloudera Data Platform (CDP) is designed to address the critical requirements for modern data architectures today and tomorrow.

IT 106

IT Unstructured Data Data Architecture Government 106

Data Engineering Weekly

DECEMBER 10, 2023

As a data practitioner, I feel OneTable is one of the critical projects in the LakeHouse era. From a data architecture point of view, this enables a lot of flexibility in integrating multiple systems. Stores metadata to utilize later. Audits using Psyberg metadata ensure data integrity and completeness.

Data Engineering 76

Data Engineering Data Engineer Engineering Metadata 76

Snowflake

DECEMBER 12, 2023

To give customers flexibility for how they fit Snowflake into their data architecture, Iceberg Tables can be configured to use either Snowflake or an external service such as AWS Glue as the table’s catalog to track metadata, with an easy, one-line SQL command to convert the table’s catalog to Snowflake in a metadata-only operation.

Metadata 83

Metadata Python AWS Government 83

Rockset

JULY 21, 2020

Metadata services used for service discovery are close to the bottom of that stack and they need to provide 1 or 2 orders of magnitude higher reliability than any service built on top of that. In your application stack, assume for every level you have in your stack, you will lose one 9 in your application’s reliability.

Data Architecture 40

Data Architecture Architecture Building Programming Language 40

Data Engineering Weekly

DECEMBER 29, 2022

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 metadata management , to be precise.

Metadata 62

Metadata Data Warehouse ETL Tools Data Workflow 62

Databand.ai

JULY 19, 2023

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.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Monte Carlo

MARCH 13, 2024

When to implement data governance Data governance is now considered a must-have for most organizations because it helps improve compliance with GDPR and other measures, safeguard proprietary data against bad actors, support a distributed data architecture, and maintain data quality.

Data Governance 52

Data Governance Government Metadata Data 52

Ascend.io

FEBRUARY 28, 2024

Metadata Management for Enhanced Machine Interpretation Data engineering extends its importance to the realm of metadata management, providing AI models with essential context about data definitions, classifications, and governance policies.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Monte Carlo

FEBRUARY 9, 2023

Over the past several years, data warehouses have evolved dramatically, but that doesn’t mean the fundamentals underpinning sound data architecture needs to be thrown out the window. Pie Insurance , a leading small business insurtech, leverages a data vault 2.0 How do you implement a data vault architecture?

Architecture 52

Architecture Raw Data Metadata Data Warehouse 52

Snowflake

NOVEMBER 2, 2023

And, since historically tools and commercial platforms were often designed to align with one specific architecture pattern, organizations struggled to adapt to changing business needs – which of course has implications on data architecture.

Data Lake 84

Data Lake Data Warehouse Cloud Unstructured Data 84

Ascend.io

APRIL 19, 2023

By adopting a post-modern data stack, engineering leaders can reduce their reliance on a multitude of vendors (and the exorbitant costs that accompany them) and open-source tools, minimize time-consuming integration work, and accelerate their overall data architecture.

Metadata 52

Metadata Business Analyst Hadoop Software Engineer 52

Data Engineering Podcast

SEPTEMBER 23, 2018

Can you walk through the stages of an ideal lifecycle for data within the context of an organizations uses for it? What are some of the common mistakes that are made when designing a data architecture and how do they lead to failure?

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Monte Carlo

MAY 25, 2023

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.

Metadata 52

Metadata Data Governance Government Business Intelligence 52

Databand.ai

AUGUST 30, 2023

A DataOps architecture is the structural foundation that supports the implementation of DataOps principles within an organization. It encompasses the systems, tools, and processes that enable businesses to manage their data more efficiently and effectively. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Cloudyard

MARCH 4, 2023

Read Time: 5 Minute, 16 Second As we know Snowflake has introduced latest badge “Data Cloud Deployment Framework” which helps to understand knowledge in designing, deploying, and managing the Snowflake landscape. Leverage the MERGE command to get the latest data in the Business layer.

Architecture 52

Architecture Cloud Metadata Data Ingestion 52

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. The communication between business units and data professionals is usually incomplete and inconsistent. Introduction to Data Mesh. Source: Thoughtworks.

Pharmaceutical 98

Pharmaceutical Data Lake Data Architecture Scala 98

Snowflake

JANUARY 22, 2024

In 2020, Fidelity kicked off its digital transformation and established an Enterprise Data Lake (EDL) along with Data Labs. All of Fidelity’s storage abides by its data security framework and data governance policies, and provides a holistic approach to metadata management.

Engineering 61

Engineering Data Lake Unstructured Data Metadata 61

The Modern Data Company

MARCH 1, 2024

For today’s Chief Data Officers (CDOs) and data teams, the struggle is real. We’re drowning in data yet thirsting for actionable insights. We need a new approach, a paradigm shift that delivers data with the agility and efficiency of a speedboat – enter Data Products.

Database-centric 40

Database-centric Data Lake Government Retail 40

Towards Data Science

OCTOBER 25, 2023

Not too long ago, almost all data architectures 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.

Data Pipeline 84

Data Pipeline SQL Data Architecture Data 84

Data Engineering Podcast

SEPTEMBER 1, 2021

That leaves DataOps reactive to data quality issues and can make your consumers lose confidence in your data. By connecting to your pipeline orchestrator like Apache Airflow and centralizing your end-to-end metadata, Databand.ai lets you identify data quality issues and their root causes from a single dashboard.

Data Lake 100

Data Lake Cloud AWS SQL 100

Monte Carlo

DECEMBER 8, 2023

Enter: data provenance and data lineage. Data lineage is a visual tool that tracks the movement and transformations of data through various systems, processes, and applications. Data provenance is the record of metadata from data’s original sources, providing the historical context and authenticity of data.

Metadata 52

Metadata Data Data Warehouse Government 52

Monte Carlo

DECEMBER 8, 2023

Enter: data provenance and data lineage. Data lineage is a visual tool that tracks the movement and transformations of data through various systems, processes, and applications. Data provenance is the record of metadata from data’s original sources, providing the historical context and authenticity of data.

Metadata 52

Metadata Data Data Warehouse Government 52

Meltano

DECEMBER 7, 2022

ELT is becoming the default choice for data architectures and yet, many best practices focus primarily on “T”: the transformations. But the extract and load phase is where data quality is determined for transformation and beyond. Source system: Metadata about where the data was extracted from.

Raw Data 52

Raw Data Metadata Data Database 52

Data Engineering Weekly

JANUARY 15, 2023

SiliconANGLE theCUBE: Analyst Predictions 2023 - The Future of Data Management By far one of the best analyses of trends in Data Management. 2023 predictions from the panel are; Unified metadata becomes kingmaker. The names hold less meaning to the outcome, but its fancy. link] All rights reserved ProtoGrowth Inc, India.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Monte Carlo

FEBRUARY 19, 2024

When data mesh doesn’t work: Lack of domain talent density Business domains have overlapping product needs Your data org is too small You have a fragmented data platform Every reliable data architecture needs reliable data What’s a data mesh again? How do we get the data we need faster?

Architecture 59

Architecture Government Data Data Architecture 59

know.bi

JUNE 15, 2022

Functionality : since the start of the project in 2019, metadata management has been drastically improved, and tons of functionality has been added to Apache Hop. A lot of new transforms and actions have appeared, and Apache Hop integrates a lot better with existing data architectures.

Metadata 52

Metadata Data Integration Cloud Storage Project 52

Cloudera

OCTOBER 11, 2022

First you need the data analytics, data management, and data science tools. They all should work on shared data of any type – with common metadata management – ideally open. We believe the best path is with a hybrid data platform for modern data architectures with data anywhere.

Data Science 89

Data Science Aggregated Data Data Consulting 89

Cloudera

JANUARY 5, 2023

This is where leveraging modern data architectures like data lakehouse, data fabric, and data mesh is essential to driving business efficiencies across diverse operations. These features provide businesses with a common metadata, security, and governance model across all their data.

Banking 52

Banking Machine Learning Insurance Data Architecture 52

Cloudera

MARCH 17, 2023

As the use of ChatGPT becomes more prevalent, I frequently encounter customers and data users citing ChatGPT’s responses in their discussions. I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics.

Education 60

Education Unstructured Data Data Lake Data Warehouse 60

Data Engineering Podcast

JULY 28, 2019

In this episode Tim Ward, CEO of CluedIn, explains the idea of eventual connectivity as a new paradigm for data integration. 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.

Data Integration 100

Data Integration Metadata Media Architecture 100

Monte Carlo

JANUARY 23, 2023

But while most every company would consider themselves a “data-first” organization, not every data architecture is treated to the same level of democratization and scalability. In this post we’ll look at the dizzyingly buzzy data mesh and how it stacks up to the more traditional aggregated architectural approach of a data lake.

Data Lake 52

Data Lake Business Intelligence Unstructured Data Architecture 52

Cloudera

SEPTEMBER 15, 2022

The consumption of the data should be supported through an elastic delivery layer that aligns with demand, but also provides the flexibility to present the data in a physical format that aligns with the analytic application, ranging from the more traditional data warehouse view to a graph view in support of relationship analysis.

Data Lake 78

Data Lake Analytics Application Cloud Storage Architecture 78

Data Engineering Podcast

AUGUST 5, 2019

We have partnered with organizations such as O’Reilly Media, Dataversity, the Open Data Science Conference, and Corinium Intelligence. Upcoming events include the O’Reilly AI Conference, the Strata Data Conference, and the combined events of the Data Architecture Summit and Graphorum.

PostgreSQL 100

PostgreSQL MongoDB Metadata Media 100

Towards Data Science

FEBRUARY 15, 2023

In this context, data management in an organization is a key point for the success of its projects involving data. One of the main aspects of correct data management is the definition of a data architecture. show() The history object is a Spark Data Frame. delta_table.history().select("version",

Data Lake 82

Data Lake Data Warehouse Hadoop Data Architecture 82

AltexSoft

NOVEMBER 10, 2021

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. What is a data lakehouse? That’s why we will rely on their expertise and vision to explain the architectural pattern of lakehouses.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52