Data Engineering Podcast

DECEMBER 4, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management 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.

Business Intelligence 100

Business Intelligence Metadata BI MongoDB 100

Data Engineering Podcast

NOVEMBER 27, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management 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. Missing data? Stale dashboards?

Data Process 100

Data Process Process Metadata Business Intelligence 100

Data Engineering Podcast

AUGUST 28, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management 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.

Data Engineering 100

Data Engineering Data Engineer MongoDB Metadata 100

Data Engineering Podcast

DECEMBER 25, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management 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. Missing data? Stale dashboards?

Building 100

Building Metadata Business Intelligence Data Lake 100

François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. With this 3rd platform generation, you have more real time data analytics and a cost reduction because it is easier to manage this infrastructure in the cloud thanks to managed services. What you have to code is this workflow !

Technology 130

Technology Architecture Google Cloud Metadata 130

Data Engineering Podcast

OCTOBER 9, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management 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.

Metadata 100

Metadata AWS MongoDB MySQL 100

Data Engineering Podcast

SEPTEMBER 4, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management 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.

IT 100

IT Metadata MongoDB MySQL 100

Data Engineering Podcast

AUGUST 6, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management 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. Sifflet also offers a 2-week free trial.

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

ProjectPro

FEBRUARY 8, 2023

It offers a simple and efficient solution for data processing in organizations. It offers users a data integration tool that organizes data from many sources, formats it, and stores it in a single repository, such as data lakes, data warehouses, etc., being data exactly matches the classifier, and 0.0

AWS 98

AWS Scala Metadata Data Lake 98

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore). Tables are governed as per agreed upon company standards.

Big Data 78

Big Data Data Management Management Metadata 78

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Engineering 92

Data Engineering Data Engineer Cloud Engineering 92

Data Engineering Weekly

JANUARY 6, 2023

Author: Chris Ricommni Recap Github: [link] [Don't forget to star it] I’m excited to release Recap , a dead simple data catalog for engineers written in Python. Recap makes it easy for engineers to build infrastructure and tools that need metadata. Unlike traditional data catalogs, Recap is designed to power software.

Metadata 40

Metadata ETL Tools MySQL Data Lake 40

AltexSoft

NOVEMBER 23, 2021

If the transformation step comes after loading (for example, when data is consolidated in a data lake or a data lakehouse ), the process is known as ELT. You can learn more about how such data pipelines are built in our video about data engineering.

Process 69

Process Data Lake Metadata Data Warehouse 69

Silectis

JANUARY 3, 2021

Data Architecture Data architecture is a composition of models, rules, and standards for all data systems and interactions between them. Data Catalog An organized inventory of data assets relying on metadata to help with data management.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

NOVEMBER 7, 2022

Metadata database. A metadata database stores information about user permissions, past and current DAG and task runs, DAG configurations, and more. By default, Airflow handles metadata with SQLite which is meant for development only. For production purposes, choose from PostgreSQL 10+, MySQL 8+, and MsSQL.

PostgreSQL 52

PostgreSQL Metadata Python MySQL 52

AltexSoft

MAY 12, 2023

A fixed schema means the structure and organization of the data are predetermined and consistent. It is commonly stored in relational database management systems (DBMSs) such as SQL Server, Oracle, and MySQL, and is managed by data analysts and database administrators. Google Cloud Storage can also be used as a data lake system.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Rockset

NOVEMBER 28, 2022

By being part of the ingest transformation, you get the power and flexibility of Rockset’s data ingestion platform to bring this CDC data from any of our supported sources including event streams, directly through our write API, or even through data lakes like S3, GCS, and Azure Blob Storage.

Data Warehouse 52

Data Warehouse PostgreSQL MongoDB Data Pipeline 52

AltexSoft

JUNE 26, 2023

According to the 2023 Stack Overflow survey , the most popular SQL solutions so far are PostgreSQL, MySQL, SQLite, and Microsoft SQL Server. Non-relational databases , on the other hand, work for data forms and structures other than tables. They are more scalable than SQL ones and capable of handling larger data volumes.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

JANUARY 31, 2023

Why is HDFS only suitable for large data sets and not the correct tool for many small files? NameNode is often given a large space to contain metadata for large-scale files. The metadata should come from a single file for optimal space use and economic benefit. And storing these metadata in RAM will become problematic.

Big Data 52

Big Data Hadoop AWS Relational Database 52

AltexSoft

OCTOBER 8, 2021

They are applied to retrieve data from the source systems, perform transformations when necessary, and load it into a target system ( data mart , data warehouse, or data lake). So, why is data integration such a big deal? Connections to both data warehouses and data lakes are possible in any case.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

AUGUST 24, 2021

In this project, you will explore the usage of Databricks Spark on Azure with Spark SQL and build this data pipeline. Upload it to Azure Data lake storage manually. Create a Data Factory pipeline to ingest files. Also, you get a chance to explore Azure Databricks, Data Factory, and Storage services.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JULY 23, 2021

For example, one of the Lambda functions will invoke the metadata in the image uploaded. For this real-time AWS project, you will leverage AWS tools such as Amazon Dynamo DB, Lambda, Aurora, MySQL, and Kinesis to put together optimum solutions for website monitoring. Create an AWS EC2 instance and install Amazon Kinesis on it.

AWS 52

AWS Project Amazon Web Services Cloud Computing 52

ProjectPro

AUGUST 21, 2015

i) Data Ingestion – The foremost step in deploying big data solutions is to extract data from different sources which could be an Enterprise Resource Planning System like SAP, any CRM like Salesforce or Siebel , RDBMS like MySQL or Oracle, or could be the log files, flat files, documents, images, social media feeds.

Hadoop 40

Hadoop Big Data Metadata Java 40