Ascend.io

NOVEMBER 28, 2023

The terms ‘data orchestration’ and ‘data pipeline orchestration’ are often used interchangeably, yet they diverge significantly in function and scope. Data orchestration refers to a wide collection of methods and tools that coordinate any and all types of data-related computing tasks.

Data Pipeline 52

Data Pipeline IT Data Metadata 52

Ascend.io

MARCH 17, 2023

These engineering functions are almost exclusively concerned with data pipelines, spanning ingestion, transformation, orchestration, and observation — all the way to data product delivery to the business tools and downstream applications. Pipelines need to grow faster than the cost to run them.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Ascend.io

MARCH 17, 2023

These engineering functions are almost exclusively concerned with data pipelines, spanning ingestion, transformation, orchestration, and observation — all the way to data product delivery to the business tools and downstream applications. Pipelines need to grow faster than the cost to run them.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Data Engineering Podcast

JULY 28, 2019

In this episode Tim Ward, CEO of CluedIn, explains the idea of eventual connectivity as a new paradigm for data integration. Rather than manually defining all of the mappings ahead of time, we can rely on the power of graph databases and some strategic metadata to allow connections to occur as the data becomes available.

Data Integration 100

Data Integration Metadata Media Architecture 100

Precisely

JULY 21, 2023

Confluent data streams help accelerate innovation for data and analytics initiatives – but only when sourcing from data you can trust. Precisely – the global leader in data integrity and a proud Connect with Confluent program member – helps you build trust in your data to derive the insights your business users need.

Data Integration 52

Data Integration Kafka Bytes Banking 52

Ascend.io

FEBRUARY 2, 2023

2, 2023 — Ascend.io, the leader in Data Pipeline Automation for building the world’s most intelligent data pipelines, is expanding its global presence and has hired Robin Rostratter as Head of EMEA sales to better engage and support the company’s customer base across Europe. . SAN FRANCISCO , Feb.

Data Pipeline 52

Data Pipeline Google Cloud Metadata Media 52

Ascend.io

FEBRUARY 2, 2023

2, 2023 — Ascend.io, the leader in Data Pipeline Automation for building the world’s most intelligent data pipelines, is expanding its global presence and has hired Robin Rostratter as Head of EMEA sales to better engage and support the company’s customer base across Europe. . SAN FRANCISCO , Feb.

Data Pipeline 52

Data Pipeline Google Cloud Metadata Media 52

Netflix Tech

NOVEMBER 14, 2023

We’ll discuss batch data processing, the limitations we faced, and how Psyberg emerged as a solution. Furthermore, we’ll delve into the inner workings of Psyberg, its unique features, and how it integrates into our data pipelining workflows. This is mainly used to identify new changes since the last update.

Data Engineering 105

Data Engineering Data Engineer Engineering Metadata 105

Data Engineering Podcast

NOVEMBER 20, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. The biggest challenge with modern data systems is understanding what data you have, where it is located, and who is using it.

Systems 130

Systems Metadata Data Pipeline MongoDB 130

Netflix Tech

NOVEMBER 14, 2023

Now, let’s explore the state of our pipelines after incorporating Psyberg. Pipelines After Psyberg Let’s explore how different modes of Psyberg could help with a multistep data pipeline. The session metadata table can then be read to determine the pipeline input.

Metadata 97

Metadata Data Pipeline Scala Data Workflow 97

AltexSoft

OCTOBER 8, 2021

What’s more, that data comes in different forms and its volumes keep growing rapidly every day — hence the name of Big Data. The good news is, businesses can choose the path of data integration to make the most out of the available information. Data integration in a nutshell. Data integration process.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

Monte Carlo

MAY 14, 2024

At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files. Table formats incorporate aspects like columns, rows, data types, and relationships, but can also include information about the structure of the data itself.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Data Engineering Podcast

DECEMBER 25, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan's active metadata capabilities. Struggling with broken pipelines? Missing data? Again, be prepared to have metadata challenges especially.

Building 100

Building Metadata Business Intelligence Data Lake 100

Ascend.io

FEBRUARY 28, 2024

Engineers ensure the availability of clean, structured data, a necessity for AI systems to learn from patterns, make accurate predictions, and automate decision-making processes. Through the design and maintenance of efficient data pipelines , data engineers facilitate the seamless flow and accessibility of data for AI processing.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Towards Data Science

NOVEMBER 4, 2023

I’d like to discuss some popular Data engineering questions: Modern data engineering (DE). Does your DE work well enough to fuel advanced data pipelines and Business intelligence (BI)? Are your data pipelines efficient? What is it? The downside of this approach is it’s pricing model though. Image by author.

Data Engineering 83

Data Engineering Data Engineer Engineering BI 83

Christophe Blefari

OCTOBER 20, 2023

Why data integration will never be fully solved — Anna covers a few data integration tools and tries to explain why this is such a tricky field that have issue to be resolved with only one cloud tool. With synthetic data you can then publicly seek for help among the world's data scientists.

Generalist 130

Generalist Entertainment NoSQL Datasets 130

Towards Data Science

FEBRUARY 6, 2024

Order snapshots are stored in my own development area (image by the author) To prevent my extractions from impacting performance on the operational side, I queried this data regularly and stored it in a persistent staging area (PSA) within my data warehouse. Metadata update Data products need to be understandable.

Systems 80

Systems Raw Data Metadata Data Cleanse 80

RandomTrees

FEBRUARY 6, 2024

Necessity for automation : Gen AI has the capacity to automate multiple data engineering processes, such as data integration, transformation, and pipeline creation, enabling data engineers to allocate their time to more valuable endeavors.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Netflix Tech

NOVEMBER 14, 2023

Using the summary column in snapshot metadata [see the Iceberg Metadata section in post 1 for more details], we parse out the partition information for each Iceberg snapshot of the source table. This information and other calculated metadata are stored in the psyberg_session_f table.

Data Process 90

Data Process Process Metadata Finance 90

Databand.ai

AUGUST 30, 2023

A shorter time-to-value indicates that your organization is efficient at processing and analyzing data for decision-making purposes. Monitoring this metric helps identify bottlenecks in the data pipeline and ensures timely insights are available for business users.

Data Cleanse 52

Data Cleanse Metadata High Quality Data Datasets 52

Workfall

JUNE 12, 2023

It ensures that organisations stay at the forefront by capturing every twist and turn in the data landscape. With CDC by their side, organisations unlock the power of informed decision-making, safeguard data integrity, and enable lightning-fast analytics. CDC also plays a crucial role in data integration and ETL processes.

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

Databand.ai

AUGUST 30, 2023

DataOps tools can be categorized into several types, including data integration tools, data quality tools, data catalog tools, data orchestration tools, and data monitoring tools. Data Integration Data integration is the process of collecting, transforming, and consolidating data from various sources.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Ascend.io

JANUARY 9, 2024

Ascend is the leader in Data Pipeline Automation for building the world’s most intelligent data pipelines. It’s a single platform with intelligence to detect and propagate change across your ecosystem, ensure data accuracy and quantify the cost of your data products. About Ascend.io

IT 52

IT Algorithm Data Pipeline Metadata 52

Data Engineering Podcast

JANUARY 15, 2022

Today’s episode is Sponsored by Prophecy.io – the low-code data engineering platform for the cloud. Prophecy provides an easy-to-use visual interface to design & deploy data pipelines on Apache Spark & Apache Airflow. You can observe your pipelines with built in metadata search and column level lineage.

Engineering 100

Engineering Electronics ETL Tools Data Pipeline 100

Data Engineering Podcast

MARCH 22, 2021

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. Once you sign up and create an alert in Datafold for your company data, they will send you a cool water flask.

Data Warehouse 100

Data Warehouse Metadata Data Lake Hadoop 100

dbt Developer Hub

JANUARY 23, 2023

Testing the quality of data in your warehouse is an important aspect in any mature data pipeline. One of the biggest blockers for developing a successful data quality pipeline is aggregating test failures and successes in an informational and actionable way. However, ensuring actionability can be challenging.

Metadata 52

Metadata High Quality Data SQL Data Integration 52

Ascend.io

MAY 23, 2023

The data engineering world is full of tips and tricks on how to handle specific patterns that recur with every data pipeline. To avoid the problems related to orphaned datasets, many data teams institute rigorous data hygiene standards and time-consuming change management procedures. How can you up your game?

Datasets 52

Datasets Data Pipeline Metadata Database 52

Ascend.io

AUGUST 16, 2023

August 16, 2023 — Ascend.io , the leader in data pipeline automation, today released an economic analysis report conducted by Enterprise Strategy Group (ESG) of its Data Pipeline Automation Platform. As enterprise usage of data analytics grows, the field has become a significant area of IT expenditure.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Pipeline 52

Data Engineering Podcast

FEBRUARY 13, 2022

Today’s episode is Sponsored by Prophecy.io – the low-code data engineering platform for the cloud. Prophecy provides an easy-to-use visual interface to design & deploy data pipelines on Apache Spark & Apache Airflow. You can observe your pipelines with built in metadata search and column level lineage.

Building 100

Building Hadoop Data Pipeline Metadata 100

Databand.ai

AUGUST 30, 2023

This requires implementing robust data integration tools and practices, such as data validation, data cleansing, and metadata management. These practices help ensure that the data being ingested is accurate, complete, and consistent across all sources.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Ascend.io

JUNE 8, 2023

The Essential Six Capabilities To set the stage for impactful and trustworthy data products in your organization, you need to invest in six foundational capabilities. Data pipelines Data integrity Data lineage Data stewardship Data catalog Data product costing Let’s review each one in detail.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Monte Carlo

NOVEMBER 14, 2023

Databricks announced that Delta tables metadata will also be compatible with the Iceberg format, and Snowflake has also been moving aggressively to integrate with Iceberg. How Apache Iceberg tables structure metadata. As with any table format, Apache Iceberg tables are only as useful and reliable as the data stored in them.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

DataKitchen

OCTOBER 20, 2023

The Solution: ‘Payload’ Data Journeys Traditional Data Observability usually focuses on a ‘process journey,’ tracking the performance and status of data pipelines. ’ It assigns unique identifiers to each data item—referred to as ‘payloads’—related to each event.

Insurance 67

Insurance Pharmaceutical Data Data Ingestion 67

ProjectPro

JANUARY 24, 2023

AWS Glue based on several aspects to help you choose the right platform for your big data project needs. What is Azure Data Factory? Azure Data Factory is a cloud-based data integration tool that lets you build data-driven processes in the cloud to orchestrate and automate data transfer and transformation.

AWS 52

AWS Cloud Amazon Web Services ETL Tools 52

Databand.ai

AUGUST 30, 2023

Integrating these principles with data operation-specific requirements creates a more agile atmosphere that supports faster development cycles while maintaining high quality standards. This demands the implementation of advanced data integration techniques, such as real-time streaming ingestion, batch processing, and API-based access.

Data Governance 40

Data Governance Data Cleanse Government Data Pipeline 40

Monte Carlo

DECEMBER 8, 2023

Enter: data provenance and data lineage. Data lineage is a visual tool that tracks the movement and transformations of data through various systems, processes, and applications. Data provenance is the record of metadata from data’s original sources, providing the historical context and authenticity of data.

Metadata 52

Metadata Data Data Warehouse Government 52

Monte Carlo

DECEMBER 8, 2023

Enter: data provenance and data lineage. Data lineage is a visual tool that tracks the movement and transformations of data through various systems, processes, and applications. Data provenance is the record of metadata from data’s original sources, providing the historical context and authenticity of data.

Metadata 52

Metadata Data Data Warehouse Government 52