Data Engineering Podcast

NOVEMBER 27, 2021

In the same way that application performance monitoring ensures reliable software and keeps application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. Start trusting your data with Monte Carlo today! Hightouch is the easiest way to sync data into the platforms that your business teams rely on.

Data Warehouse 100

Data Warehouse Data Lake BI Business Intelligence 100

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. Let us first get a clear understanding of why Data Science is important. What is the need for Data Science?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Monte Carlo

APRIL 24, 2023

While we won’t get into the minutia of every consideration for every level of the data stack, it’s important to recall these five considerations as they’ll nonetheless steer the direction of our conversation. There are two primary types of raw data. Your data team and your customers will thank you.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

dbt Developer Hub

APRIL 24, 2023

One example of a popular drag-and-drop transformation tool is Alteryx which allows business analysts to transform data by dragging and dropping operators in a canvas. In this sense, dbt may be a more suitable solution to building resilient and modular data pipelines due to its focus on data modeling.

BI 83

BI Data Workflow SQL Data Pipeline 83

Monte Carlo

JUNE 14, 2023

The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Monte Carlo

MARCH 24, 2023

Sure, terabytes or even petabytes of data are involved, but generally it’s not the size of the data but everything surrounding the data–workflows, access permissions, layers of dependencies–that pose data migration risks. Here are some tips for mitigating some of the risks of data migration.

Data Warehouse 52

Data Warehouse AWS Cloud Data Governance 52

phData: Data Engineering

MAY 11, 2023

The highly repeatable and uni-directional flow of data means that a simple approach can be taken with analytics while still maintaining basic rigor to protect the integrity of the workflows built. In addition, breaking the human and data workflows into modular components enables this simplification.

Coding 52

Coding Software Engineer Software Engineering Government 52

phData: Data Engineering

JANUARY 3, 2022

This commonly introduces: Database or Data Warehouse API/EDI Integrations ETL software Business intelligence tooling By leveraging off-the-shelf tooling, your company separates disciplines by technology. This required applying transformations and filters to the data for various business units.

IT 52

IT AWS Software Engineer Software Engineering 52

Databand.ai

DECEMBER 29, 2022

Her proprietary methodology fuses the art of data storytelling and visualization to drive users to take action. Mico’s ability to help companies gain ROI from their business intelligence investments has been sought out by Fortune 500 companies. Mico actively posts about data analytics, BI strategy, and data storytelling.

BI 52

BI Consulting Data Science Data Governance 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59