Data Engineering Podcast

JUNE 5, 2022

The team at Skyflow decided that the second best way is to build a storage system dedicated to securely managing your sensitive information and making it easy to integrate with your applications and data systems. Atlan is the metadata hub for your data ecosystem. Atlan is the metadata hub for your data ecosystem.

Data Security 100

Data Security Metadata MongoDB Scala 100

Christophe Blefari

JANUARY 20, 2024

The main difference between both is the fact that your computation resides in your warehouse with SQL rather than outside with a programming language loading data in memory. In this category I recommend also to have a look at data ingestion (Airbyte, Fivetran, etc.), workflows (Airflow, Prefect, Dagster, etc.)

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Data Engineering Weekly

MAY 16, 2023

In the second part, we will focus on architectural patterns to implement data quality from a data contract perspective. Why is Data Quality Expensive? I won’t bore you with the importance of data quality in the blog. But before doing that, let's revisit some of the basic theories of the data pipeline.

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

Cloudera

AUGUST 26, 2021

While we walk through the steps one by one from data ingestion to analysis, we will also demonstrate how Ozone can serve as an ‘S3’ compatible object store. Learn more about the impacts of global data sharing in this blog, The Ethics of Data Exchange. Data ingestion through ‘s3’. Ozone Namespace Overview.

Data Science 107

Data Science Cloud Hadoop Metadata 107

Towards Data Science

DECEMBER 1, 2023

Technical Overview The project architecture is depicted as follows: Google Calendar -> Fivetran -> Snowflake -> dbt -> Snowflake Dashboard , with GitHub Actions orchestrating the deployment. Ingestion —  Fivetran Data ingestion can be configured from both Fivetran and Snowflake using the Partner Connect feature.

Data Engineering 74

Data Engineering Data Engineer Project Engineering 74

RandomTrees

SEPTEMBER 6, 2020

Lot of cloud-based data warehouses are available in the market today, out of which let us focus on Snowflake. Snowflake is an analytical data warehouse that is provided as Software-as-a-Service (SaaS). Built on new SQL database engine, it provides a unique architecture designed for the cloud.

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

LinkedIn Engineering

DECEMBER 12, 2023

Pinot is a columnar OLAP store that serves analytics queries on data ingested from realtime streams. PEDAL also consists of a metadata store that holds various algorithmic parameters, including the scale of noise that we introduce and whether we should use one-shot or continual observation algorithms.

Algorithm 77

Algorithm Metadata SQL Datasets 77

Data Engineering Podcast

AUGUST 6, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Databand.ai

JUNE 28, 2023

They’re betting their business on it and that the data pipelines that run it will continue to work. Context is crucial (and often lacking) A major cause of data quality issues and pipeline failures are transformations within those pipelines. Most data architecture today is opaque—you can’t tell what’s happening inside.

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Data Engineering Podcast

JUNE 19, 2022

Summary Metadata is the lifeblood of your data platform, providing information about what is happening in your systems. In order to level up their value a new trend of active metadata is being implemented, allowing use cases like keeping BI reports up to date, auto-scaling your warehouses, and automated data governance.

Metadata 130

Metadata MongoDB Scala MySQL 130

Cloudera

SEPTEMBER 28, 2020

Cloudera has found that customers have spent many years investing in their big data assets and want to continue to build on that investment by moving towards a more modern architecture that helps leverage the multiple form factors. Data Science and machine learning workloads using CDSW. Background: . on roadmap).

Cloud 130

Cloud Kafka Professional Services Metadata 130

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 67

Data Warehouse Cloud Kafka Cloud Storage 67

Cloudera

AUGUST 31, 2021

Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Consideration of both data & metadata in the migration.

Data Warehouse 80

Data Warehouse Database-centric Metadata Cloud 80

ProjectPro

FEBRUARY 25, 2022

Efficient Scheduling and Runtime Increased Adaptability and Scope Faster Analysis and Real-Time Prediction Introduction to the Machine Learning Pipeline Architecture How to Build an End-to-End a Machine Learning Pipeline? The final sample used for training and testing the model is the output of data preprocessing.

Machine Learning 52

Machine Learning Building Amazon Web Services AWS 52

dbt Developer Hub

JANUARY 14, 2023

The builder: I’m a data freelancer who deploys end to end solutions, so when I have a data problem, I cannot just let it go. dlt is a new Python library for declarative data ingestion which I have wanted to test for some time. The dlt pipeline I created for ingestion is in this repo.

Data Ingestion 52

Data Ingestion Google Cloud Python Cloud 52

Silectis

JANUARY 3, 2021

Big Query Google’s cloud data warehouse. 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

Maxime Beauchemin

JANUARY 20, 2017

It also becomes the role of the data engineering team to be a “center of excellence” through the definitions of standards, best practices and certification processes for data objects. In a fast growing, rapidly evolving, slightly chaotic data ecosystem, metadata management and tooling become a vital component of a modern data platform.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

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. Respective Cloud would consume/Store the data in bucket or containers. Snowpipe to automate the ingestion process.

Architecture 52

Architecture Cloud Metadata Data Ingestion 52

Knowledge Hut

SEPTEMBER 29, 2023

By combining data from various structured and unstructured data systems into structures, Microsoft Azure Data Engineers will be able to create analytics solutions. Why Should You Get an Azure Data Engineer Certification? You can browse the data lake files with the interactive training material.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested.

Architecture 96

Architecture Metadata Unstructured Data Machine Learning 96

Zalando Engineering

OCTOBER 23, 2017

This is done in conjunction with our Fashion Librarians (data stewardships) curation guidelines. Accessibility - Ease of data onboarding, and data exposure and consumption are cornerstones of SPP. As well as ensuring data supplies can onboard data easily, we need to ensure the same ease of access for all our data consumers.

Media 40

Media Manufacturing Data Ingestion Metadata 40

Data Engineering Podcast

NOVEMBER 20, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Data Lake 130

Data Lake Data Ingestion MongoDB Scala 130

Snowflake

NOVEMBER 29, 2023

Also, the associated business metadata for omics, which make it findable for later use, are dynamic and complex and need to be captured separately. Additionally, the fact that they need to be standardized makes the data discovery effort challenging for downstream analysis.

Metadata 84

Metadata Healthcare Medical Data Storage 84

Rockset

AUGUST 28, 2023

Streaming first architectures are a necessary foundation for the AI era. Query across your ANN indexes on vector embeddings, and your JSON and geospatial “metadata” fields efficiently. Spin a Virtual Instance for streaming data ingestion. If you know SQL, you already know how to use Rockset.

Metadata 78

Metadata Unstructured Data SQL Database 78

Cloudera

DECEMBER 20, 2021

In the past year, the Bank of the West has begun using the Cloudera platform to establish a data governance and security framework to manage and protect its customers’ sensitive information. The platform is centralizing the data, data management & governance, and building custom controls for data ingestion into the system.

Government 85

Government Data Security Banking Metadata 85

Netflix Tech

DECEMBER 21, 2020

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture.

Data Warehouse 81

Data Warehouse Metadata Algorithm Data 81

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. These tools help organizations implement DataOps practices by providing a unified platform for data teams to collaborate, share, and manage their data assets.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Netflix Tech

MARCH 25, 2019

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Nonetheless, Netflix data landscape (see below) is complex and many teams collaborate effectively for sharing the responsibility of our data system management.

Building 87

Building Metadata Transportation Data Ingestion 87

Cloudera

JUNE 30, 2022

With Cloudera’s vision of hybrid data , enterprises adopting an open data lakehouse can easily get application interoperability and portability to and from on premises environments and any public cloud without worrying about data scaling. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 83

Data Lake Business Intelligence Metadata Data Warehouse 83

ProjectPro

FEBRUARY 8, 2023

Let us dive deeper into this data integration solution by AWS and understand how and why big data professionals leverage it in their data engineering projects. When Glue receives a trigger, it collects the data, transforms it using code that Glue generates automatically, and then loads it into Amazon S3 or Amazon Redshift.

AWS 98

AWS Scala Metadata Data Lake 98

Towards Data Science

JULY 24, 2023

Closely related to this is how those same platforms are bundling or unbundling related data services from data ingestion and transformation to data governance and monitoring. Why are these things related, and more importantly, why should data leaders care? Take data governance for example.

Metadata 97

Metadata Data Warehouse Data Lake Data Science 97

Ascend.io

MARCH 14, 2023

Data represents our present and our future, and therein lies a significant problem: the more data you’re dealing with, the more challenging it will be to scale your company in a sustainable and standardized way. It provides a more distributed, decentralized, and resilient approach to data management. So, what’s the solution?

Government 52

Government Architecture Data Lake Data 52

Ascend.io

MARCH 14, 2023

Data represents our present and our future, and therein lies a significant problem: the more data you’re dealing with, the more challenging it will be to scale your company in a sustainable and standardized way. It provides a more distributed, decentralized, and resilient approach to data management. So, what’s the solution?

Government 52

Government Architecture Data Lake Data 52

Cloudera

MARCH 31, 2021

With the addition of Google Cloud, we deliver on our vision of providing a hybrid and multi-cloud architecture to support our customer’s analytics needs regardless of deployment platform. . Data Preparation (Apache Spark and Apache Hive) .

Google Cloud 89

Google Cloud Cloud Amazon Web Services Cloud Storage 89

ProjectPro

AUGUST 24, 2021

If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of best data engineering project examples below. With the trending advance of IoT in every facet of life, technology has enabled us to handle a large amount of data ingested with high velocity.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52