Data Engineering Podcast

JULY 3, 2022

Summary The perennial challenge of data engineers is ensuring that information is integrated reliably. In order to quickly identify if and how two data systems are out of sync Gleb Mezhanskiy and Simon Eskildsen partnered to create the open source data-diff utility. In fact, while only 3.5%

Data Integration 100

Data Integration MongoDB Scala MySQL 100

Data Engineering Podcast

SEPTEMBER 4, 2022

In this episode Gopal Erinjippurath discusses the data engineering challenges of building and serving those data sets, and how they are distilling complex climate information into consumable facts so you don’t have to be an expert to understand it. In fact, while only 3.5% That’s where our friends at Ascend.io

MongoDB 100

MongoDB Scala MySQL Data Ingestion 100

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Databand.ai

AUGUST 30, 2023

The core philosophy of DataOps is to treat data as a valuable asset that must be managed and processed efficiently. It emphasizes the importance of collaboration between different teams, such as data engineers, data scientists, and business analysts, to ensure that everyone has access to the right data at the right time.

Data Governance 52

Data Governance Data Pipeline Government Data Cleanse 52

Monte Carlo

DECEMBER 13, 2023

“Schema change monitors are critical because we aren’t always informed by the engineering team about schema changes in the source database,” Daniel says. Thanks to Monte Carlo, we can detect these issues very quickly — most of the time, even before our data workflow fails, so users aren’t impacted.

BI 52

BI Data Ingestion SQL Data Warehouse 52

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

Monte Carlo

APRIL 24, 2023

In this article, we’ll dive deep into the data presentation layers of the data stack to consider how scale impacts our build versus buy decisions, and how we can thoughtfully apply our five considerations at various points in our platform’s maturity to find the right mix of components for our organizations unique business needs.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Ascend.io

DECEMBER 21, 2022

21, 2022 – Ascend.io , The Data Automation Cloud, today announced they have partnered with Snowflake , the Data Cloud company, to launch Free Ingest , a new feature that will reduce an enterprise’s data ingest cost and deliver data products up to 7x faster by ingesting data from all sources into the Snowflake Data Cloud quickly and easily.

Data Ingestion 52

Data Ingestion Google Cloud Data Lake Cloud 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. Table of Contents The Common Threads: Ingest, Transform, Share Before we explore the differences between the ETL process and a data pipeline , let’s acknowledge their shared DNA.

Data Pipeline 52

Data Pipeline ETL Tools Pipeline-centric Data Warehouse 52

Monte Carlo

MAY 25, 2023

Data orchestration helps companies comply with various international privacy laws and regulations, many of which require companies to demonstrate the source and rationale for their data collection. As data volume grows, scheduling becomes critical to successfully managing your data ingestion and transformation jobs.

Data Pipeline 52

Data Pipeline Data Workflow Data Data Governance 52

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? For example, data may be extracted from multiple sources, reorganized, and joined at different times before ultimately being served to its final destination. Why is data pipeline architecture important? They also recently acquired Apache Flink , another streaming solution.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Ascend.io

MAY 19, 2023

Picture a data engineering leader, like a captain at the helm of a ship, navigating the vast ocean of data. The modern data stack promised a vessel with cutting-edge navigation tools to sail smoothly through this ocean. In our case, data ingestion, transformation, orchestration, reverse ETL, and observability.

Data Pipeline 52

Data Pipeline Data Engineering Data Engineer Media 52

Ascend.io

MARCH 17, 2023

As a result, stakeholders limit their reliance on data, making decisions based on gut instinct rather than facts. To shift this harmful approach, companies need to make fundamental changes to their data engineering function and start running at speed and with agility. And that leaves them with one choice.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Ascend.io

MARCH 17, 2023

As a result, stakeholders limit their reliance on data, making decisions based on gut instinct rather than facts. To shift this harmful approach, companies need to make fundamental changes to their data engineering function and start running at speed and with agility. And that leaves them with one choice.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

phData: Data Engineering

JANUARY 3, 2022

Software engineering practices define how to reliably and effectively build software and data products, delivering value faster to your customers. In this post, we will explore the complexities involved with software engineering with a focus on data engineering and data operations (DataOps).

IT 52

IT AWS Software Engineer Software Engineering 52

Snowflake

MARCH 27, 2023

Introducing CARTO Workflows Snowflake’s powerful data ingestion and transformation features help many data engineers and analysts who prefer SQL. Workflows automates not only geospatial processes, but other data workflows as well.

Generalist 52

Generalist Raw Data Business Analyst SQL 52

AltexSoft

MARCH 14, 2023

That’s why some MDS tools are commercial distributions designed to be low-code or even no-code, making them accessible to data practitioners with minimal technical expertise. This means that companies don’t necessarily need a large data engineering team. Data democratization.

IT 59

IT Data Warehouse Data Governance Data Lake 59