Ascend.io

NOVEMBER 14, 2024

Why Future-Proofing Your Data Pipelines Matters Data has become the backbone of decision-making in businesses across the globe. The ability to harness and analyze data effectively can make or break a company’s competitive edge. Resilience and adaptability are the cornerstones of a future-proof data pipeline.

Data Pipeline 52

Data Pipeline Amazon Web Services Data Integration Data 52

Data Science Blog: Data Engineering

MAY 20, 2024

Continuous Integration and Continuous Delivery (CI/CD) for Data Pipelines: It is a Game-Changer with AnalyticsCreator! The need for efficient and reliable data pipelines is paramount in data science and data engineering. They transform data into a consistent format for users to consume.

Data Pipeline 52

Data Pipeline BI Data Lake Data Warehouse 52

Data Engineering Podcast

MAY 1, 2022

Atlan is a collaborative workspace for data-driven teams, like Github for engineering or Figma for design teams. If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Data Warehouse 100

Data Warehouse Data Integration Cloud Google Cloud 100

Data Engineering Podcast

JUNE 25, 2023

[Rudderstack]([link] RudderStack provides all your customer data pipelines in one platform. You can collect, transform, and route data across your entire stack with its event streaming, ETL, and reverse ETL pipelines. Rudderstack]([link] RudderStack provides all your customer data pipelines in one platform.

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Data Engineering Data Engineer Python Engineering 225

Data Engineering Podcast

FEBRUARY 18, 2024

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Data lakes are notoriously complex. Multiple open source projects and vendors have been working together to make this vision a reality.

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Data Lake High Quality Data Data Warehouse Google Cloud 262

Data Engineering Podcast

JANUARY 1, 2022

In this episode Emily Riederer shares her work to create a controlled vocabulary for managing the semantic elements of the data managed by her team and encoding it in the schema definitions in her data warehouse. Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Data Warehouse 100

Data Warehouse BI Data Workflow Data Engineering 100

Data Engineering Podcast

FEBRUARY 8, 2021

In this episode Zeeshan Qureshi and Michelle Ark share their experiences using DBT to manage the data warehouse for Shopify. Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code. What kinds of data sources are you working with?

Data Warehouse 100

Data Warehouse Building BI SQL 100

Christophe Blefari

MARCH 15, 2024

With yato you give a folder with SQL queries and it guesses the DAG and runs the queries in the right order. BigQuery supports DELETE to delete partitions in a SQL query. Arrow doing a lot of the data operation heavy lifting. Give a lot of insights on the market. this is more common sense but always works.

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Metadata Datasets Data Data Warehouse 272

Data Engineering Podcast

OCTOBER 14, 2019

Summary Managing a data warehouse can be challenging, especially when trying to maintain a common set of patterns. They provide an AWS-native, serverless, data infrastructure that installs in your VPC. Datacoral helps data engineers build and manage the flow of data pipelines without having to manage any infrastructure.

Data Warehouse 100

Data Warehouse PostgreSQL AWS Programming Language 100

Hevo

FEBRUARY 9, 2023

Data Build Tool (DBT) is a powerful, SQL-based open-source tool. It helps organizations quickly build and maintain data transformations in their data pipelines. Building data pipelines is challenging, as we […]

Data Pipeline 52

Data Pipeline Building Data Warehouse Data Storage 52

Monte Carlo

AUGUST 25, 2023

Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 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

Ascend.io

MAY 31, 2023

In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. Fast forward to the present day, and we now have data pipelines. Data Ingestion Data ingestion is the first step of both ETL and data pipelines.

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Data Pipeline ETL Tools Pipeline-centric Data Warehouse 52

Cloudera

JUNE 2, 2021

Data pipelines are in high demand in today’s data-driven organizations. As critical elements in supplying trusted, curated, and usable data for end-to-end analytic and machine learning workflows, the role of data pipelines is becoming indispensable.

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Data Pipeline Data Warehouse Machine Learning Data Architect 94

ProjectPro

JUNE 16, 2022

An AWS data pipeline helps businesses move and unify their data to support several data-driven initiatives. It enables flow from a data lake to an analytics database or an application to a data warehouse. This blog will teach you about AWS Data Pipeline, its architecture, components, and benefits.

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Data Pipeline AWS Amazon Web Services Data Consolidation 59

Monte Carlo

FEBRUARY 6, 2023

So, you’re planning a cloud data warehouse migration. But be warned, a warehouse migration isn’t for the faint of heart. As you probably already know if you’re reading this, a data warehouse migration is the process of moving data from one warehouse to another. A worthy quest to be sure.

Data Warehouse 52

Data Warehouse AWS Data Validation Data 52

Monte Carlo

JANUARY 25, 2023

In this article, Chad Sanderson , Head of Product, Data Platform , at Convoy and creator of Data Quality Camp , introduces a new application of data contracts: in your data warehouse. In the last couple of posts , I’ve focused on implementing data contracts in production services.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. Table of Contents What is a Data Pipeline? The Importance of a Data Pipeline What is an ETL Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Workfall

AUGUST 14, 2023

Reading Time: 7 minutes In today’s data-driven world, efficient data pipelines have become the backbone of successful organizations. These pipelines ensure that data flows smoothly from various sources to its intended destinations, enabling businesses to make informed decisions and gain valuable insights.

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Data Pipeline Data Raw Data Database 62

Engineering at Meta

NOVEMBER 30, 2022

UPM is our internal standalone library to perform static analysis of SQL code and enhance SQL authoring. UPM takes SQL code as input and represents it as a data structure called a semantic tree. A limiting type system: Initially, we used only the fixed set of built-in Hive data types ( string , integer , boolean , etc. )

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SQL Data Warehouse Coding Metadata 70

DataKitchen

JULY 27, 2023

The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure. While working in Azure with our customers, we have noticed several standard Azure tools people use to develop data pipelines and ETL or ELT processes. We counted ten ‘standard’ ways to transform and set up batch data pipelines in Microsoft Azure.

Data Pipeline 52

Data Pipeline BI Machine Learning Data Preparation 52

Monte Carlo

APRIL 24, 2023

During data ingestion, raw data is extracted from sources and ferried to either a staging server for transformation or directly into the storage level of your data stack—usually in the form of a data warehouse or data lake. There are two primary types of raw data. Missed Nishith’s 5 considerations?

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Data Engineering Weekly

JULY 5, 2023

link] Policy Genius: Data Warehouse Testing Strategies for Better Data Quality Data Testing and Data Observability are widely discussed topics in Data Engineering Weekly. Can we test SQL business logic during the development phase itself? Perhaps unit test the pipeline?

Data Warehouse 52

Data Warehouse Database Data Pipeline SQL 52

Data Engineering Podcast

JANUARY 21, 2024

A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

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Data Lake High Quality Data NoSQL Data Warehouse 147

Data Engineering Podcast

DECEMBER 28, 2022

Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. Monitoring data quality, tracing incidents, and testing changes can be daunting and often takes hours to days or even weeks. Sign up free at dataengineeringpodcast.com/rudder Build Data Pipelines.

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Data Lake Data Warehouse Data Pipeline MongoDB 130

Data Engineering Podcast

JANUARY 8, 2023

In this episode Ori Rafael explains how they are automating the creation and scheduling of orchestration flows and their related transforations in a unified SQL interface. Data engineers struggling with unreliable data need look no further than Monte Carlo, the leading end-to-end Data Observability Platform! Missing data?

PostgreSQL 130

PostgreSQL Data Lake Data Warehouse BI 130

Snowflake

OCTOBER 16, 2024

Many of our customers — from Marriott to AT&T — start their journey with the Snowflake AI Data Cloud by migrating their data warehousing workloads to the platform. Today we’re focusing on customers who migrated from a legacy data warehouse to Snowflake and some of the benefits they saw.

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Digital Media Media Data Lake Data Warehouse 81

Data Engineering Podcast

DECEMBER 25, 2022

Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. Monitoring data quality, tracing incidents, and testing changes can be daunting and often takes hours to days or even weeks. Sign up free at dataengineeringpodcast.com/rudder Build Data Pipelines.

Machine Learning 130

Machine Learning Systems Data Lake Data Warehouse 130

Cloudera

SEPTEMBER 9, 2018

We are proud to announce the general availability of Cloudera Altus Data Warehouse , the only cloud data warehousing service that brings the warehouse to the data. Modern data warehousing for the cloud. Modern data warehousing for the cloud. Using Cloudera Altus for your cloud data warehouse.

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Data Warehouse Metadata Cloud Storage Cloud 40

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Monte Carlo

JULY 9, 2024

Known for its columnar storage, vectorized query execution, and scale-up approach to SQL analytics, DuckDB fans proclaim it’s faster, more efficient, and more affordable than other databases. MotherDuck turbocharged DuckDB’s efficiency with multiplayer cloud analytics, making it a lightweight but powerful data warehouse.

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Data Warehouse Data Pipeline SQL Database 69

ThoughtSpot

OCTOBER 27, 2023

Every business that analyzes their operational (or transactional) data needs to build a custom data pipeline involving several batch or streaming jobs to extract transactional data from relational databases , transform it, and load it into the data warehouse. Enter a name for the SQL View and click Save.

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Building MySQL Data Warehouse SQL 97

Data Engineering Podcast

JANUARY 15, 2023

With a PostgreSQL-compatible interface, you can now work with real-time data using ANSI SQL including the ability to perform multi-way complex joins, which support stream-to-stream, stream-to-table, table-to-table, and more, all in standard SQL.

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Coding Building PostgreSQL Data Lake 130

Towards Data Science

MARCH 6, 2023

On-premise and cloud working together to deliver a data product Photo by Toro Tseleng on Unsplash Developing a data pipeline is somewhat similar to playing with lego, you mentalize what needs to be achieved (the data requirements), choose the pieces (software, tools, platforms), and fit them together. Google Cloud.

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Google Cloud Cloud Storage Data Pipeline Cloud 82

Christophe Blefari

JANUARY 20, 2024

Data engineering inherits from years of data practices in US big companies. Hadoop initially led the way with Big Data and distributed computing on-premise to finally land on Modern Data Stack — in the cloud — with a data warehouse at the center. Sometime with transformation.

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Data Engineering Data Engineer Engineering Hadoop 130

Data Engineering Podcast

NOVEMBER 27, 2022

In this episode Matt Jaffee explains how to model your data as bitmaps and the benefits that this representation provides for fast aggregate computation. Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. or any other destination you choose. Pricing for SQLake is simple.

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Data Lake Data Warehouse MongoDB Data Pipeline 100

DareData

JULY 29, 2020

With these points in mind, I argue that the biggest hurdle to the widespread adoption of these advanced techniques in the healthcare industry is not intrinsic to the industry itself, or in any way related to its practitioners or patients, but simply the current lack of high-quality data pipelines. What makes a good Data Pipeline?

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Healthcare Data Pipeline Medical Pipeline-centric 52