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

FEBRUARY 20, 2022

Summary The life sciences as an industry has seen incredible growth in scale and sophistication, along with the advances in data technology that make it possible to analyze massive amounts of genomic information. You can observe your pipelines with built in metadata search and column level lineage.

Systems 100

Systems Software Engineer Software Engineering Data Warehouse 100

Workfall

JUNE 12, 2023

Moreover, it facilitates the implementation of microservices architectures and event-driven systems, automating reactions to data changes without manual intervention. In real-time data streaming and event-driven architectures, CDC captures data changes to trigger actions or workflows.

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

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.

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Data Engineering Podcast

APRIL 5, 2021

It builds your customer data warehouse and your identity graph on your data warehouse, with support for Snowflake, Google BigQuery, Amazon Redshift, and more. Their SDKs and plugins make event streaming easy, and their integrations with cloud applications like Salesforce and ZenDesk help you go beyond event streaming.

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Data Engineering Podcast

AUGUST 5, 2019

Finding the data that you need is tricky, and Amundsen will help you solve that problem. And as your data grows in volume and complexity, there are foundational principles that you can follow to keep data workflows streamlined. Finding the data that you need is tricky, and Amundsen will help you solve that problem.

PostgreSQL 100

PostgreSQL MongoDB Metadata Media 100

Data Engineering Weekly

JANUARY 15, 2023

SiliconANGLE theCUBE: Analyst Predictions 2023 - The Future of Data Management By far one of the best analyses of trends in Data Management. 2023 predictions from the panel are; Unified metadata becomes kingmaker. The author walked through various strategies, from sync to async job submission and batch job submission strategy.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

dbt Developer Hub

OCTOBER 14, 2021

It uses the dbt Cloud Metadata API to surface metadata from dbt right in Hex, letting you quickly get the context you need on things like data freshness without juggling multiple apps and browser tabs. Modeling behavioral data with Snowplow and dbt (coming up on 10/27). Hex just launched an integration with dbt!

Metadata 52

Metadata BI Software Engineer Software Engineering 52

Ascend.io

DECEMBER 11, 2023

Data orchestration is the process of efficiently coordinating the movement and processing of data across multiple, disparate systems and services within a company. This contrasts with data pipeline orchestration , which adopts a narrower focus, centering on the construction, operation, and management of data pipelines.

Data Workflow 52

Data Workflow Data Pipeline Data Lake Data 52

Monte Carlo

AUGUST 13, 2024

Here’s how Gartner officially defines the category of data observability tools: “Data observability tools are software applications that enable organizations to understand the state and health of their data, data pipelines, data landscapes, data infrastructures, and the financial operational cost of the data across distributed environments.

Data 52

Data Data Warehouse Data Pipeline Data Architecture 52

Hepta Analytics

FEBRUARY 14, 2022

Disadvantages of a data lake are: Can easily become a data swamp data has no versioning Same data with incompatible schemas is a problem without versioning Has no metadata associated It is difficult to join the data Data warehouse stores processed data, mostly structured data.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Cloudera

AUGUST 21, 2020

For example, if a credit card was used in the United States and shortly afterward the same card was used in Spain to withdraw the same amount, these two events in isolation could appear legitimate. However, in the context of time and geography, these two events point to a pattern of fraud.

Banking 62

Banking Kafka Cloud Storage Government 62

Netflix Tech

OCTOBER 18, 2022

With the high growth of workflows in the past few years?—?increasing increasing at > 100% a year, the need for a scalable data workflow orchestrator has become paramount for Netflix’s business needs. A workflow instance is an execution of a workflow, similarly, an execution of a step is called a step instance.

Java 83

Java Data Machine Learning Systems 83

Netflix Tech

NOVEMBER 20, 2023

This enables auto propagation of backfill data in multi-stage pipelines. Netflix Maestro Maestro is the Netflix data workflow orchestration platform built to meet the current and future needs of Netflix. As we know, an iceberg table contains a list of snapshots with a set of metadata data.

Process 86

Process Data Pipeline Datasets SQL 86

AltexSoft

JUNE 7, 2021

A HDFS Master Node, called a NameNode , keeps metadata with critical information about system files (like their names, locations, number of data blocks in the file, etc.) and keeps track of storage capacity, a volume of data being transferred, etc. Among solutions facilitation data management are. Apache Hadoop ecosystem.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

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

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. Analysis of logs, metrics, and security events. Real-time behavior modeling with ML.

Engineering 52

Engineering NoSQL Programming Language Java 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

Monte Carlo

JUNE 14, 2023

Airbyte – An open source platform that easily allows you to sync data from applications. Data streaming ingestion solutions include: Apache Kafka – Confluent is the vendor that supports Kafka, the open source event streaming platform to handle streaming analytics and data ingestion.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Edureka

JULY 3, 2024

You can extract data efficiently and once gathered, you can transform this data using built-in or custom transformations, and then load it into your desired destination. The orchestration capabilities take the chore out of large-scale data operation management across your entire organization.

Pipeline-centric 52

Pipeline-centric Data Lake Database-centric Data Pipeline 52

AltexSoft

MARCH 14, 2023

Moreover, over 20 percent of surveyed companies were found to be utilizing 1,000 or more data sources to provide data to analytics systems. These sources commonly include databases, SaaS products, and event streams. Databases store key information that powers a company’s product, such as user data and product data.

IT 59

IT Data Warehouse Data Governance Data Lake 59