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

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

Data Engineering Weekly

OCTOBER 30, 2022

Editor’s Note: The current state of the Data Catalog The results are out for our poll on the current state of the Data Catalogs. The highlights are that 59% of folks think data catalogs are sometimes helpful. We saw in the Data Catalog poll how far it has to go to be helpful and active within a data workflow.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Ingestion 52

Ascend.io

JULY 3, 2024

This methodology emphasizes automation, collaboration, and continuous improvement, ensuring faster, more reliable data workflows. With data workflows growing in scale and complexity, data teams often struggle to keep up with the increasing volume, variety, and velocity of data. Let’s dive in!

Data Workflow 52

Data Workflow Data Pipeline Data Data Engineer 52

DataKitchen

MAY 10, 2024

The Third of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset. Examples include regular loading of CRM data and anomaly detection.

Raw Data 53

Raw Data Data Ingestion Datasets Data 53

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

OCTOBER 28, 2024

Tools like Python’s requests library or ETL/ELT tools can facilitate data enrichment by automating the retrieval and merging of external data. Read More: Discover how to build a data pipeline in 6 steps Data Integration Data integration involves combining data from different sources into a single, unified view.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

Databand.ai

AUGUST 30, 2023

Automation plays a critical role in the DataOps framework, as it enables organizations to streamline their data management and analytics processes and reduce the potential for human error. This can be achieved through the use of automated data ingestion, transformation, and analysis tools.

Data Governance 52

Data Governance Data Pipeline Government Business Analyst 52

Knowledge Hut

NOVEMBER 2, 2023

Top 10 Azure Data Engineering Project Ideas for Beginners For beginners looking to gain practical experience in Azure Data Engineering, here are 10 Azure Data engineer real time projects ideas that cover various aspects of data processing, storage, analysis, and visualization using Azure services: 1.

Data Engineer 52

Data Engineer Data Engineering Project Coding 52

Ascend.io

MAY 31, 2023

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 Ingestion Data ingestion is the first step of both ETL and data pipelines.

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

Hevo

AUGUST 16, 2024

This blog explores the world of open source data orchestration tools, highlighting their importance in managing and automating complex data workflows. From Apache Airflow to Google Cloud Composer, we’ll walk you through ten powerful tools to streamline your data processes, enhance efficiency, and scale your growing needs.

Google Cloud 52

Google Cloud Data Workflow Data Data Engineer 52

Knowledge Hut

SEPTEMBER 25, 2023

Data Engineer Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure. Work together with data scientists and analysts to understand the needs for data and create effective data workflows.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Lake 52

Monte Carlo

DECEMBER 13, 2023

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. Georvic Tur , Senior Data Engineer at Tools for Humanity, uses Performance dashboards to make sure his team’s real-time data ingestions are running correctly.

BI 52

BI Data Ingestion SQL Data Warehouse 52

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? Databricks – Databricks, the Apache Spark-as-a-service platform, has pioneered the data lakehouse, giving users the options to leverage both structured and unstructured data and offers the low-cost storage features of a data lake.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Knowledge Hut

MARCH 28, 2024

Role Level: Intermediate Responsibilities Design and develop big data solutions using Azure services like Azure HDInsight, Azure Databricks, and Azure Data Lake Storage. Implement data ingestion, processing, and analysis pipelines for large-scale data sets.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Warehouse 52

AltexSoft

SEPTEMBER 21, 2023

The Elastic Stacks Elasticsearch is integral within analytics stacks, collaborating seamlessly with other tools developed by Elastic to manage the entire data workflow — from ingestion to visualization. This means that Elasticsearch can be easily integrated into different modern data stacks.

Engineering 52

Engineering NoSQL Programming Language Java 52

Ascend.io

MAY 19, 2023

In our case, data ingestion, transformation, orchestration, reverse ETL, and observability. This is the modern data stack as we know it today. The modern data stack has become disjointed and complex, slowing data engineering’s productivity and limiting their ability to provide value to the business.

Data Pipeline 52

Data Pipeline Data Engineer Data Engineering Media 52

Ascend.io

MARCH 17, 2023

Data quality rules, or assertions, should be configurable at every processing step in every pipeline and evaluate every data record. Value Catching data problems in real-time avoids costly reruns and delays. It reduces the amount of rework arising from after-the- fact quality reviews and simplifies data workflows.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Ascend.io

MARCH 17, 2023

Data quality rules, or assertions, should be configurable at every processing step in every pipeline and evaluate every data record. Value Catching data problems in real-time avoids costly reruns and delays. It reduces the amount of rework arising from after-the- fact quality reviews and simplifies data workflows.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

phData: Data Engineering

JANUARY 3, 2022

We recommend identifying sync points that align with your information architecture so that data currency expectations are known at a governance level. This helps drive requirements and determines the right validation at the right time for the data. There are significant pros and cons to both approaches.

IT 52

IT AWS Software Engineer Software Engineering 52

Knowledge Hut

SEPTEMBER 29, 2023

Why Should You Get an Azure Data Engineer Certification? Becoming an Azure data engineer allows you to seamlessly blend the roles of a data analyst and a data scientist. One of the pivotal responsibilities is managing data workflows and pipelines, a core aspect of a data engineer's role.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

AltexSoft

MARCH 14, 2023

Data orchestration involves managing the scheduling and execution of data workflows. As for this part, Apache Airflow is a popular open-source platform choice used for data orchestration across the entire data pipeline.

IT 59

IT Data Warehouse Data Governance Data Lake 59

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

Data Engineering Weekly

DECEMBER 18, 2024

These New Age Data IDEs will be characterized by: Seamless Integration: They will seamlessly integrate the entire data lifecycle, from data ingestion and transformation to analysis, visualization, and deployment, all within a unified environment. Tools like lakebyte.ai are the beginning of such a revolution.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Lake 52