Monte Carlo

JULY 27, 2023

These specialists are also commonly referred to as data reliability engineers. To be successful in their role, data quality engineers will need to gather data quality requirements (mentioned in 65% of job postings) from relevant stakeholders.

Engineering 52

Engineering Healthcare Scala Data Warehouse 52

Data Engineering Podcast

FEBRUARY 18, 2024

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Data lakes are notoriously complex. Multiple open source projects and vendors have been working together to make this vision a reality.

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

Data Engineering Podcast

FEBRUARY 4, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Dagster offers a new approach to building and running data platforms and data pipelines. Starburst : ![Starburst

SQL 173

SQL Data Lake High Quality Data Data Pipeline 173

DataKitchen

JANUARY 3, 2022

They need high-quality data in an answer-ready format to address many scenarios with minimal keyboarding. What they are getting from IT and other data sources is, in reality, poor-quality data in a format that requires manual customization. A lot of industries talk about bringing data together in data hubs.

Business Analyst 98

Business Analyst Data Lake Consulting Data Analytics 98

Data Engineering Podcast

JANUARY 21, 2024

A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

Monte Carlo

APRIL 24, 2023

During data ingestion, raw data is extracted from sources and ferried to either a staging server for transformation or directly into the storage level of your data stack—usually in the form of a data warehouse or data lake. There are two primary types of raw data. Missed Nishith’s 5 considerations?

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Monte Carlo

MAY 25, 2023

Picture this: your data is scattered. Data pipelines originate in multiple places and terminate in various silos across your organization. Your data is inconsistent, ungoverned, inaccessible, and difficult to use. Some of the value companies can generate from data orchestration tools include: Faster time-to-insights.

Data Pipeline 52

Data Pipeline Data Workflow Data Data Governance 52