Ascend.io

AUGUST 31, 2023

In this article, we assess: The role of the data warehouse on one hand, and the data lake on the other; The features of ETL and ELT in these two architectures; The evolution to EtLT; The emerging role of data pipelines. Let’s take a closer look.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Ascend.io

JUNE 8, 2023

The Essential Six Capabilities To set the stage for impactful and trustworthy data products in your organization, you need to invest in six foundational capabilities. Data pipelines Data integrity Data lineage Data stewardship Data catalog Data product costing Let’s review each one in detail.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Striim

JANUARY 4, 2023

A data contract is a formal agreement between the users of a source system and the data engineering team that is extracting data for a data pipeline. This data is loaded into a data repository — such as a data warehouse — where it can be transformed for end users. temperature).

PostgreSQL 52

PostgreSQL Data Warehouse Data Lake Data 52

Databand.ai

NOVEMBER 4, 2022

Re-Imagining Data Observability Ryan Yackel 2022-11-04 10:36:35 Data observability has become one of the hottest topics of the year – and for good reason. Data observability provides an end-to-end view into exactly what’s happening with data pipelines across an organization’s data fabric.

Data 52

Data Data Pipeline Retail Metadata 52

RandomTrees

SEPTEMBER 6, 2020

A combination of structured and semi structured data can be used for analysis and loaded into the cloud database without the need of transforming into a fixed relational scheme first. This stage handles all the aspects of data storage like organization, file size, structure, compression, metadata, statistics.

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

Monte Carlo

JANUARY 25, 2023

The contracts themselves should be created using well-established protocols for serializing and deserializing structured data such as Google’s Protocol Buffers (protobuf), Apache Avro, or even JSON. We can specify the fields of the contract in addition to metadata like ownership, SLA, and where the table is located.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

ProjectPro

JANUARY 31, 2023

Data Variety Hadoop stores structured, semi-structured and unstructured data. RDBMS stores structured data. Data storage Hadoop stores large data sets. RDBMS stores the average amount of data. Works with only structured data. Hardware Hadoop uses commodity hardware.

Big Data 52

Big Data Hadoop AWS Relational Database 52