Cloudera

FEBRUARY 8, 2021

Below is the entire set of steps in the data lifecycle, and each step in the lifecycle will be supported by a dedicated blog post(see Fig. 1): Data Collection – data ingestion and monitoring at the edge (whether the edge be industrial sensors or people in a vehicle showroom). 2 ECC data enrichment pipeline.

Data Pipeline 118

Data Pipeline Building Manufacturing Data Warehouse 118

Striim

SEPTEMBER 11, 2024

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. We’ll answer the question, “What are data pipelines?” Table of Contents What are Data Pipelines?

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

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). Multiple open source projects and vendors have been working together to make this vision a reality.

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

Data Engineering Podcast

OCTOBER 28, 2021

In the same way that application performance monitoring ensures reliable software and keeps application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. Start trusting your data with Monte Carlo today! Hightouch is the easiest way to sync data into the platforms that your business teams rely on.

Data Pipeline 100

Data Pipeline SQL Data Warehouse Data Lake 100

Christophe Blefari

MARCH 15, 2024

Forward thinking Dataviz is hierarchical — Malloy, once again, provides an excellent article about a new way to see data visualisations. Coding data pipelines is faster than renting connector catalogs — This is something I've always believed. It's inspirational.

Metadata 272

Metadata Data Data Warehouse Software Engineer 272

Databand.ai

JUNE 28, 2023

Data Pipeline Observability: A Model For Data Engineers Eitan Chazbani June 29, 2023 Data pipeline observability is your ability to monitor and understand the state of a data pipeline at any time. We believe the world’s data pipelines need better data observability.

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Data Engineering Podcast

APRIL 19, 2021

Summary Most of the time when you think about a data pipeline or ETL job what comes to mind is a purely mechanistic progression of functions that move data from point A to point B. Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Data Pipeline 100

Data Pipeline Machine Learning Data Warehouse Datasets 100

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

APRIL 23, 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.

Data Lake 277

Data Lake Kafka Machine Learning Data Warehouse 277

Simon Späti

MARCH 9, 2021

This post focuses on practical data pipelines with examples from web-scraping real-estates, uploading them to S3 with MinIO, Spark and Delta Lake, adding some Data Science magic with Jupyter Notebooks, ingesting into Data Warehouse Apache Druid, visualising dashboards with Superset and managing everything with Dagster.

Data Engineering 189

Data Engineering Data Engineer Engineering Project 189

Data Engineering Podcast

JUNE 1, 2021

Summary Every part of the business relies on data, yet only a small team has the context and expertise to build and maintain workflows and data pipelines to transform, clean, and integrate it. RudderStack’s smart customer data pipeline is warehouse-first.

Data Pipeline 100

Data Pipeline Data Warehouse Data Data Engineering 100

Data Engineering Podcast

MAY 1, 2022

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. Struggling with broken pipelines? Struggling with broken pipelines?

Data Warehouse 100

Data Warehouse Data Integration Cloud Google Cloud 100

Monte Carlo

OCTOBER 31, 2024

AI data engineers are data engineers that are responsible for developing and managing data pipelines that support AI and GenAI data products. Essential Skills for AI Data Engineers Expertise in Data Pipelines and ETL Processes A foundational skill for data engineers?

Data Engineering 52

Data Engineering Data Engineer Engineering Unstructured Data 52

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.

Data Engineering 225

Data Engineering Data Engineer Python Engineering 225

Cloudera

JUNE 17, 2022

In the second blog of the Universal Data Distribution blog series , we explored how Cloudera DataFlow for the Public Cloud (CDF-PC) can help you implement use cases like data lakehouse and data warehouse ingest, cybersecurity, and log optimization, as well as IoT and streaming data collection.

Data Pipeline 94

Data Pipeline Building Kafka Java 94

Striim

NOVEMBER 19, 2024

This fully managed service leverages Striim Cloud’s integration with the Microsoft Fabric stack for seamless data mirroring to Fabric Data Warehouse and Lake House. Microsoft Azure Fabric is an end-to-end analytics and data platform designed for enterprises that require a unified solution. Striim automates the rest.

SQL 52

SQL Database Data Warehouse Data Pipeline 52

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.

Google Cloud 98

Google Cloud Cloud Storage Data Pipeline Cloud 98

Analytics Vidhya

APRIL 3, 2023

Introduction Companies can access a large pool of data in the modern business environment, and using this data in real-time may produce insightful results that can spur corporate success. Real-time dashboards such as GCP provide strong data visualization and actionable information for decision-makers.

Data Engineering 258

Data Engineering Data Engineer Engineering Data 258

Data Engineering Podcast

APRIL 9, 2023

When it was difficult to wire together the event collection, data modeling, reporting, and activation it made sense to buy monolithic products that handled every stage of the customer data lifecycle. Now that the data warehouse has taken center stage a new approach of composable customer data platforms is emerging.

Data Lake 147

Data Lake Data Warehouse Machine Learning Data 147

Start Data Engineering

OCTOBER 12, 2021

Introduction Responsibilities of a data engineer 1. Move data between systems 2. Manage data warehouse 3. Schedule, execute, and monitor data pipelines 4. Serve data to the end-users 5. Data strategy for the company 6.

Data Engineering 130

Data Engineering Data Engineer Engineering Data Warehouse 130

Striim

MARCH 21, 2025

Batch processing: data is typically extracted from databases at the end of the day, saved to disk for transformation, and then loaded in batch to a data warehouse. Batch data integration is useful for data that isn’t extremely time-sensitive. Electric bills are a relevant example.

Process 52

Process Data Warehouse Kafka Data Pipeline 52

Simon Späti

MARCH 9, 2021

This post focuses on practical data pipelines with examples from web-scraping real-estates, uploading them to S3 with MinIO, Spark and Delta Lake, adding some Data Science magic with Jupyter Notebooks, ingesting into Data Warehouse Apache Druid, visualising dashboards with Superset and managing everything with Dagster.

Data Engineering 130

Data Engineering Data Engineer Engineering Project 130

Engineering at Meta

FEBRUARY 4, 2025

Meta joins the Data Transfer Project and has continuously led the development of shared technologies that enable users to port their data from one platform to another. 2024: Users can access data logs in Download Your Information. What are data logs?

Accessible 80

Accessible Accessibility Raw Data Data Warehouse 80

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. RudderStack helps you build a customer data platform on your warehouse or data lake.

Data Lake 130

Data Lake Data Warehouse Data Pipeline MongoDB 130

Striim

OCTOBER 11, 2024

A well-executed data pipeline can make or break your company’s ability to leverage real-time insights and stay competitive. Thriving in today’s world requires building modern data pipelines that make moving data and extracting valuable insights quick and simple. What is a Data Pipeline?

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Data Engineering Podcast

FEBRUARY 4, 2024

Dagster offers a new approach to building and running data platforms and data pipelines. What are the situations where RisingWave can/should be a system of record vs. a point-in-time view of data in transit, with a data warehouse/lakehouse as the longitudinal storage and query engine?

SQL 173

SQL Data Lake High Quality Data Machine Learning 173

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. RudderStack helps you build a customer data platform on your warehouse or data lake.

Machine Learning 130

Machine Learning Systems Data Lake Data Warehouse 130

Striim

AUGUST 14, 2024

When implemented effectively, smart data pipelines seamlessly integrate data from diverse sources, enabling swift analysis and actionable insights. They empower data analysts and business users alike by providing critical information while protecting sensitive production systems. What is a Smart Data Pipeline?

Data Pipeline 52

Data Pipeline Data Architecture Transportation 52

phData: Data Engineering

FEBRUARY 21, 2025

In this post, we will be particularly interested in the impact that cloud computing left on the modern data warehouse. We will explore the different options for data warehousing and how you can leverage this information to make the right decisions for your organization. Understanding the Basics What is a Data Warehouse?

Cloud 52

Cloud Data Warehouse Amazon Web Services Data Ingestion 52

Data Engineering Podcast

MAY 28, 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.

Data Lake 162

Data Lake Machine Learning Data Warehouse Education 162

Data Engineering Weekly

NOVEMBER 24, 2024

link] Jon Osborn: Best Practices for Using QUERY_TAG in Snowflake The modern data warehouses are good at running at scale, given the cost is not a constraint. The service offers configurable counter types optimized for various use cases with a unified Control Plane configuration.

Data Engineering 58

Data Engineering Data Engineer Engineering Insurance 58

Data Engineering Weekly

FEBRUARY 2, 2025

[link] Get Your Guide: From Snowflake to Databricks: Our cost-effective journey to a unified data warehouse. GetYourGuide discusses migrating its Business Intelligence (BI) data source from Snowflake to Databricks, achieving a 20% cost reduction.

Data Engineering 58

Data Engineering Data Engineer Engineering Data Lake 58

Data Engineering Podcast

MAY 14, 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.

Data Lake 147

Data Lake Machine Learning Data Warehouse AWS 147

Data Engineering Podcast

JUNE 4, 2023

How does the unified experience of Agile Data Engine change the way that teams think about the lifecycle of their data? What does CI/CD look like for a data warehouse? Can you describe how Agile Data Engine is architected? Rudderstack]([link] RudderStack provides all your customer data pipelines in one platform.

Data Engineering 130

Data Engineering Data Engineer Engineering Data Lake 130

Data Engineering Podcast

DECEMBER 18, 2022

Data engineers struggling with unreliable data need look no further than Monte Carlo, the leading end-to-end Data Observability Platform! Trusted by the data teams at Fox, JetBlue, and PagerDuty, Monte Carlo solves the costly problem of broken data pipelines.

Metadata 130

Metadata Business Intelligence Data Lake BI 130

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.

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

Monte Carlo

AUGUST 6, 2024

Data warehouses are the centralized repositories that store and manage data from various sources. They are integral to an organization’s data strategy, ensuring data accessibility, accuracy, and utility. However, beneath their surface lies a host of invisible risks embedded within the data warehouse layers.

Data Warehouse 52

Data Warehouse Raw Data Machine Learning BI 52