dbt Developer Hub

NOVEMBER 28, 2021

This could just as easily have been Snowflake or Redshift, but I chose BigQuery because one of my data sources is already there as a public dataset. dbt seeds data from offline sources and performs necessary transformations on data after it's been loaded into BigQuery. I spun up an instance using its docker/up.sh

Raw Data 52

Raw Data Metadata Database Datasets 52

Towards Data Science

JANUARY 17, 2024

Parquet vs ORC vs Avro vs Delta Lake Photo by Viktor Talashuk on Unsplash The big data world is full of various storage systems, heavily influenced by different file formats. These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction.

Big Data 70

Big Data Data Data Storage SQL 70

Ascend.io

MAY 19, 2023

For example, a global media company struggled because they were juggling different tools like Fivetran for bringing in data, dbt for transforming it, Airflow for coordinating everything, Monte Carlo for monitoring and scanning for troubled data, and Hightouch for getting data out to other systems.

Data Pipeline 52

Data Pipeline Data Engineering Data Engineer Media 52

Netflix Tech

OCTOBER 27, 2020

The data warehouse is not designed to serve point requests from microservices with low latency. Therefore, we must efficiently move data from the data warehouse to a global, low-latency and highly-reliable key-value store. Users only need to specify the data source and the destination cluster information in a YAML file.

Data Warehouse 97

Data Warehouse Datasets Data Big Data 97

Towards Data Science

FEBRUARY 15, 2023

The Data Lake architecture was proposed in a period of great growth in the data volume, especially in non-structured and semi-structured data, when traditional Data Warehouse systems start to become incapable of dealing with this demand. The data became useless. Legend says, that this didn’t go well.

Data Lake 77

Data Lake Data Warehouse Hadoop Data Architecture 77

Netflix Tech

OCTOBER 31, 2018

the Media Timeline Data Model In the previous post in this series, we described some important Netflix business needs as well as traits of the media data system?—?called The curious reader might have noticed that a majority of these characteristics relate to properties of the data managed by NMDB.

Media 54

Media Metadata Data MongoDB 54

Monte Carlo

MARCH 2, 2023

Otherwise you may produce more data anomalies than you prevent. Data Contracts Image courtesy of Andrew Jones. You can think of data contracts as circuit breakers, but for data schemas instead of the data itself. Write clear SQL statements Let’s face it, some of the SQL formatting debates are silly.

Food 52

Food Data SQL Data Pipeline 52

Monte Carlo

JANUARY 25, 2023

It can be challenging when a team is expected to take full responsibility for a key data product when there are no guarantees around the upstream data quality. Without clear management of each transformation step stretching back to source systems, teams may be unwilling to bear the responsibility of contracts.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

ProjectPro

JANUARY 31, 2023

Key features Hadoop RDBMS Overview Hadoop is an open-source software collection that links several computers to solve problems requiring large quantities of data and processing. RDBMS is a part of system software used to create and manage databases based on the relational model. RDBMS stores structured data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Zalando Engineering

SEPTEMBER 28, 2022

Also, it was based on Zalando's "Mosaic" system architecture, which was being phased out in favour of the newer Interface Framework. Interface Framework - To integrate the tool with Zalando's new architecture and design system, to leverage its capabilities and scale with it. However, it had many limitations affecting scalability.

Certification 52

Certification Architecture Data Schemas Metadata 52

Cloudera

FEBRUARY 9, 2021

Second, if the partition number is increased after the system goes live, the default Kafka partitioner will return different numbers evenly if you provide the same key, which means messages with the same key as before will be in a different partition from the previous one. . > Schema Management. > Minutes.

Data Warehouse 70

Data Warehouse Cloud Kafka Cloud Storage 70

Monte Carlo

APRIL 20, 2023

What are the data lineage use cases and best practices that will drive value for the business? Here is a list of 17 valuable data lineage use cases that can help improve data quality, incident management, democratization, system modernization, and compliance. We’re glad you asked.

Data Warehouse 52

Data Warehouse BI Data Government 52

Cloudera

JANUARY 11, 2021

In data-driven organizations, to fulfill its charter to democratize data and provide on-demand, quality computing services in a secure, compliant environment, IT must replace legacy approaches and update technologies. There needs to emerge data-first, self-service replacement for these old systems. billion dollars.’.

Data Warehouse 62

Data Warehouse Pharmaceutical Data Lake BI 62

Zalando Engineering

SEPTEMBER 8, 2021

Since they share most parts of the user journey, it was natural to explore if the Apps could benefit from a system based on Entities and Renderers, too. We want to avoid unwanted data coupling and allow Renderers to be reused in other contexts with minimal risks. We knew it would be too much of a stretch for Mosaic fragments.

Engineering 52

Engineering Computer Science Data Schemas Coding 52

ProjectPro

APRIL 26, 2016

Pig vs Hive Criteria Pig Hive Type of Data Apache Pig is usually used for semi structured data. Used for Structured Data Schema Schema is optional. Hive requires a well-defined Schema. Language It is a procedural data flow language. Hcatalog can be used to share data structures with external systems.

Hadoop 40

Hadoop Metadata SQL Database 40

Confluent

APRIL 30, 2019

This framework opens the door for various optimization techniques from the existing data stream management system (DSMS) and data stream processing literature. addSink(" SinkProcessor" , "output" , "MappingProcessor" ); System. build(properties); System. With the release of Apache Kafka ® 2.1.0, println(builder.

Kafka 89

Kafka Coding Process Bytes 89

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40