Ascend.io

JULY 11, 2024

Metadata is the information that provides context and meaning to data, ensuring it’s easily discoverable, organized, and actionable. It enhances data quality, governance, and automation, transforming raw data into valuable insights. Imagine a library with millions of books but no catalog system to organize them.

Metadata 52

Metadata IT Government High Quality Data 52

Ascend.io

DECEMBER 4, 2024

Instead of driving innovation, data engineers often find themselves bogged down with maintenance tasks. On average, engineers spend over half of their time maintaining existing systems rather than developing new solutions. Tool sprawl is another hurdle that data teams must overcome.

Data Pipeline 52

Data Pipeline Metadata Data Workflow Data 52

Data Engineering Weekly

NOVEMBER 3, 2024

Foundation Capital: A System of Agents brings Service-as-Software to life software is no longer simply a tool for organizing work; software becomes the worker itself, capable of understanding, executing, and improving upon traditionally human-delivered services. It's good to know about Dapr and restate.dev.

Data Engineering 62

Data Engineering Data Engineer Engineering Pipeline-centric 62

Data Engineering Podcast

JULY 17, 2022

Summary There are extensive and valuable data sets that are available outside the bounds of your organization. Whether that data is public, paid, or scraped it requires investment and upkeep to acquire and integrate it with your systems. Atlan is the metadata hub for your data ecosystem.

Data Management 130

Data Management Management Metadata MongoDB 130

Data Engineering Podcast

SEPTEMBER 17, 2023

Summary A significant amount of time in data engineering is dedicated to building connections and semantic meaning around pieces of information. Linked data technologies provide a means of tightly coupling metadata with raw information. What is the level of native support/compatibiliity that you see for JSON-LD in data systems?

Building 189

Building SQL BI Python 189

Data Engineering Podcast

DECEMBER 18, 2022

In this episode Abe Gong brings his experiences with the Great Expectations project and community to discuss the technical and organizational considerations involved in implementing these constraints to your data workflows. Atlan is the metadata hub for your data ecosystem. Missing data? Stale dashboards?

Metadata 130

Metadata Business Intelligence Data Lake BI 130

Data Engineering Podcast

JULY 31, 2022

Summary Data lineage is the roadmap for your data platform, providing visibility into all of the dependencies for any report, machine learning model, or data warehouse table that you are working with. Atlan is the metadata hub for your data ecosystem. Data lineage and metadata systems are a hot topic right now.

IT 100

IT Metadata MongoDB MySQL 100

Data Engineering Podcast

AUGUST 28, 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. RudderStack helps you build a customer data platform on your warehouse or data lake.

Data Engineering 100

Data Engineering Data Engineer MongoDB Metadata 100

Data Engineering Podcast

SEPTEMBER 18, 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. What are the contributing factors that lead to fragmentation of visibility for data workflows at different stages?

Building 100

Building Metadata MongoDB MySQL 100

Netflix Tech

NOVEMBER 14, 2023

Input : List of source tables and required processing mode Output : Psyberg identifies new events that have occurred since the last high watermark (HWM) and records them in the session metadata table. The session metadata table can then be read to determine the pipeline input. Audit Run various quality checks on the staged data.

Metadata 101

Metadata Data Pipeline Scala Data Process 101

Data Engineering Podcast

MAY 3, 2021

Summary The Data industry is changing rapidly, and one of the most active areas of growth is automation of data workflows. Taking cues from the DevOps movement of the past decade data professionals are orienting around the concept of DataOps. How does security factor into the design of robust DataOps systems?

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Data Engineering Podcast

APRIL 5, 2021

In this episode Prukalpa Sankar shares her experiences across multiple attempts at building a system that brings everyone onto the same page, ultimately bringing her to found Atlan. What portions of the data workflow is Atlan responsible for? What components of the data stack might Atlan replace?

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Data Engineering Weekly

DECEMBER 29, 2022

Data catalogs are the most expensive data integration systems you never intended to build. Data Catalog as a passive web portal to display metadata requires significant rethinking to adopt modern data workflow, not just adding “modern” in its prefix. It makes rolling out the data catalogs.

Metadata 62

Metadata Data Warehouse ETL Tools Data Workflow 62

AltexSoft

JUNE 7, 2021

You don’t need to archive or clean data before loading. The system automatically replicates information to prevent data loss in the case of a node failure. It doesn’t belong to the master-slave paradigm, being responsible for loading data into the cluster, describing how the data must be processed, and retrieving the output.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Workfall

JUNE 12, 2023

Change Data Capture (CDC) is a powerful technique that revolutionises data engineering by capturing and applying incremental changes to databases or data sources. It bridges gaps in data ecosystems, ensuring consistency and synchronisation across systems.

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

Netflix Tech

OCTOBER 18, 2022

Due to its popularity, the number of workflows managed by the system has grown exponentially. The scheduler on-call has to closely monitor the system during non-business hours. As the usage increased, we had to vertically scale the system to keep up and were approaching AWS instance type limits.

Java 84

Java Data Machine Learning Systems 84

Netflix Tech

OCTOBER 27, 2020

The data warehouse is not designed to serve point requests from microservices with low latency. Therefore, we must efficiently move data from the data warehouse to a global, low-latency and highly-reliable key-value store. Figure 1 shows how we use Bulldozer to move data at Netflix.

Data Warehouse 100

Data Warehouse Datasets Data Big Data 100

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 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. The current state of these systems is inherently passive systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Ascend.io

DECEMBER 11, 2023

Is your data stuck in separate areas within your company, making it hard to use effectively? Here’s the deal: for data to truly drive your business forward, you need a reliable and scalable system to keep it moving without hiccups. In other words, you need data orchestration. So, why is data orchestration a big deal?

Data Workflow 52

Data Workflow Data Pipeline Data Lake Data 52

Databand.ai

AUGUST 30, 2023

It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows. It encompasses the systems, tools, and processes that enable businesses to manage their data more efficiently and effectively. Data Sources Data sources are the backbone of any DataOps architecture.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Databand.ai

AUGUST 30, 2023

DataOps tools should provide a comprehensive data cataloging solution that allows organizations to create a centralized repository of their data assets, complete with metadata, data lineage information, and data samples. This allows it to be easily integrated with other services and systems.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Data Engineering Weekly

MARCH 11, 2023

[link] Data Engineering Weekly Data Catalog - A Broken Promise Data catalogs are the most expensive data integration systems you never intended to build.

Data Engineering 52

Data Engineering Data Engineer Engineering High Quality Data 52

Hepta Analytics

FEBRUARY 14, 2022

The multiple databases will be queried, then passed through the transformation server to transform the data to comply with the business rule then the transformed the data is stored in a data store. This is also used for legacy systems. This means that your data store has to have capabilities of transforming the data.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Monte Carlo

AUGUST 13, 2024

This is accomplished by continuously monitoring, tracking, alerting, analyzing and troubleshooting data workflows to reduce problems and prevent data errors or system downtime.” Our perspective: Gartner does a good job covering what’s being monitored and the workflows associated with data observability tools.

Data 52

Data Data Warehouse Data Pipeline Data Architecture 52

Ascend.io

MAY 19, 2023

For example, a global media company struggled because they were juggling different tools like Fivetran for bringing in data, dbt for transforming it, Airflow for coordinating everything, Monte Carlo for monitoring and scanning for troubled data, and Hightouch for getting data out to other systems.

Data Pipeline 52

Data Pipeline Data Engineering Data Engineer Media 52

Databand.ai

DECEMBER 29, 2022

Follow Mico on LinkedIn 3) Chad Sanderson Chief Operator at Data Quality Camp Chad has extensive experience in data from hyper-growth startups to established tech supergiants to small businesses just dipping their toes into ecommerce. Seth has experience in leading corporate wide strategies across complex corporate organizations.

BI 52

BI Consulting Data Science Data Governance 52

Knowledge Hut

SEPTEMBER 29, 2023

The Azure Data Engineer Certification test evaluates one's capacity for organizing and putting into practice data processing, security, and storage, as well as their capacity for keeping track of and maximizing data processing and storage. Why Should You Get an Azure Data Engineer Certification?

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

SEPTEMBER 20, 2022

Here’s how Prefect , Series B startup and creator of the popular data orchestration tool, harnessed the power of data observability to preserve headcount, improve data quality and reduce time to detection and resolution for data incidents. But Monte Carlo doesn’t stop at the “most important” tables.

Big Data 52

Big Data Data Warehouse Data Data Governance 52

AltexSoft

SEPTEMBER 21, 2023

From those home-made beginnings as Compass, Elasticsearch has matured into one of the leading enterprise search engines, standing among the top 10 most popular database management systems globally according to the Stack Overflow 2023 Developer Survey. But like any technology, it has its share of pros and cons.

Engineering 52

Engineering NoSQL Programming Language Java 52

Edureka

AUGUST 19, 2024

One of the key elements of Azure Data Factory that permits data integration between various network environments is Integration Runtime. It offers the infrastructure needed to transfer data safely between cloud and on-site data storage.

Transportation 40

Transportation Data Integration Data Storage Utilities 40

Ascend.io

MARCH 17, 2023

Theoretically, data and analytics should be the backbones of decision-making in business. Like mitochondria power a cell, data powers a business. Today, there are no intelligent systems that deliver data at the pace, and with the impact, leaders need to power the business. But for most companies, that’s not the reality.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Ascend.io

MARCH 17, 2023

Theoretically, data and analytics should be the backbones of decision-making in business. Like mitochondria power a cell, data powers a business. Today, there are no intelligent systems that deliver data at the pace, and with the impact, leaders need to power the business. But for most companies, that’s not the reality.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Monte Carlo

JUNE 14, 2023

What is data pipeline architecture? Data pipeline architecture is the process of designing how data is surfaced from its source system to the consumption layer. Data orchestration Airflow : Airflow is the most common data orchestrator used by data teams. Now Go Build Some Data Pipelines!

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Ascend.io

MARCH 19, 2025

Data pipeline observability means having robust monitoring, logging, and alerting across all pipeline components. Metadata is the foundation of observability, providing essential insights into data pipeline health, execution status, dependencies, and performance metrics. Did yesterdays data load complete successfully?

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

AltexSoft

NOVEMBER 7, 2022

DevOps tasks — for example, creating scheduled backups and restoring data from them. Airflow is especially useful for orchestrating Big Data workflows. Airflow is not a data processing tool by itself but rather an instrument to manage multiple components of data processing. Metadata database. Since the 2.0

PostgreSQL 52

PostgreSQL Metadata Python MySQL 52

Data Engineering Weekly

DECEMBER 16, 2024

Automated Data Classification and Governance LLMs are reshaping governance practices. Grab’s Metasense , Uber’s DataK9 , and Meta’s classification systems use AI to automatically categorize vast data sets, reducing manual efforts and improving accuracy.

Data Engineering 62

Data Engineering Data Engineer Engineering Unstructured Data 62