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

Data Engineering Podcast

SEPTEMBER 23, 2018

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. Can you walk through the stages of an ideal lifecycle for data within the context of an organizations uses for it?

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Cloudera

MARCH 23, 2022

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. Iceberg is designed to be open and engine agnostic allowing datasets to be shared.

Metadata 90

Metadata Data Architecture BI Machine Learning 90

Monte Carlo

MAY 25, 2023

According to a recent survey , data engineers are reporting nearly twice as many data incidents this year as last. And nearly 75% of the time, business stakeholders are the first to identify data issues. Forward-thinking data organizations are increasingly moving to adopt distributed data architectures like the data mesh.

Metadata 52

Metadata Data Governance Government Business Intelligence 52

Snowflake

JANUARY 22, 2024

Fidelity has two main enterprise data architecture guiding principles for its data scientists and data engineers: For data storage, Snowflake is the platform for storing all of the company’s structured and semi-structured analytical data in its Enterprise Data Lake and Data Labs.

Engineering 63

Engineering Data Lake Unstructured Data Metadata 63

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 90

Metadata Python AWS Government 90

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

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Architecture Metadata Government Kafka 124

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

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 Unstructured Data Business Intelligence Architecture 52

Monte Carlo

APRIL 1, 2021

Here’s where data catalogs fall short and how data discovery platforms and tools can help ensure your data lake doesn’t turn into a data swamp. Data discovery tools and platforms can help. Data discovery tools and platforms can help. Image courtesy of Adrian on Unsplash.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

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? Schema enforcement and data governance. Metadata layer. Metadata layer.

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

Monte Carlo

APRIL 20, 2023

I can surface ownership metadata and alert the relevant owners to make sure the appropriate changes are made so these breakages never happen. And over time, we’ve invested effort into cleaning up our lineages, simplifying our logic,” said SeatGeek Director of Data Engineering, Brian London. Image courtesy of Monte Carlo.

Data Warehouse 52

Data Warehouse BI Data Government 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

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Scala Data Lake BI Google Cloud 64

DataKitchen

JANUARY 23, 2023

Data lineage can also be used for compliance, auditing, and data governance purposes. DataOps Observability Five on data lineage: Data lineage traces data’s origin, history, and movement through various processing, storage, and analysis stages. What is missing in data lineage?

Data Governance 52

Data Governance Government Data Pipeline Data 52

Ascend.io

MARCH 14, 2023

We’re increasingly coming to realize that the rigid, monolithic architectures we’re currently using just don’t make the cut to store, organize, access, and use the ever-growing amounts of data. The magic of a data mesh is that it combines a data product mindset with a distributed data modeling technique.

Government 52

Government Architecture Data Lake Data 52

Ascend.io

MARCH 14, 2023

We’re increasingly coming to realize that the rigid, monolithic architectures we’re currently using just don’t make the cut to store, organize, access, and use the ever-growing amounts of data. The magic of a data mesh is that it combines a data product mindset with a distributed data modeling technique.

Government 52

Government Architecture Data Lake Data 52

Monte Carlo

JULY 30, 2020

In the age of self-service business intelligence , nearly every company considers themselves a data-first company, but not every company is treating their data architecture with the level of democratization and scalability it deserves. Your company, for one, views data as a driver of innovation.

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IT Data Lake Business Intelligence Data Architecture 45

phData: Data Engineering

JULY 18, 2023

Better Transparency: There’s more clarity about where data is coming from, where it’s going, why it’s being transformed, and how it’s being used. Improved Data Governance: This level of transparency can also enhance data governance and control mechanisms in the new data system.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Monte Carlo

JUNE 14, 2023

For example, data may be extracted from multiple sources, reorganized, and joined at different times before ultimately being served to its final destination. Why is data pipeline architecture important? Data then, and even today for some organizations, was primarily hosted in on-premises databases with non-scalable storage.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Monte Carlo

MAY 17, 2023

Data observability, an organization’s ability to fully understand the health and quality of the data in their systems, has become one of the hottest technologies in modern data engineering. Reduce The Amount Of Data Incidents Resident, an online mattress and homegoods store, has a lot of data.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Data observability, an organization’s ability to fully understand the health and quality of the data in their systems, has become one of the hottest technologies in modern data engineering. Reduce the amount of data incidents Resident, an online mattress and homegoods store, has a lot of data.

Data Pipeline 52

Data Pipeline Data Data Engineering Data Engineer 52

ProjectPro

JANUARY 31, 2022

Traditional data preparation platforms, including Apache Spark, are unnecessarily complex and inefficient, resulting in fragile and costly data pipelines. Snowflake's machine learning partners transfer most of their automated feature engineering down into Snowflake's cloud data platform.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52