Confessions of a Data Guy

DECEMBER 29, 2022

Data engineering is a vital field within the realm of data science that focuses on the practical aspects of collecting, storing, and processing large amounts of data. It involves designing and building the infrastructure to store and process data, as well as developing the tools and systems to extract valuable insights and knowledge from that […] The post I asked ChatGPT to write a blog post about Data Engineering.

Data Engineering 130

Data Engineering Data Engineer Engineering IT 130

Seattle Data Guy

DECEMBER 29, 2022

AWS has jumped on the bandwagon of removing the need for ETLs. Snowflake announced this both with their hybrid tables and their partnership with Salesforce. Now, I do take a little issue with the naming “Zero ETLs”. Because at the very surface the functionality described is often closer to a zero integration future, which probably… Read more The post Should We Get Rid Of ETLs?

AWS 130

AWS Consulting Big Data Data 130

KDnuggets

DECEMBER 29, 2022

This article compiles the 38 top Python libraries for data science, data visualization & machine learning, as best determined by KDnuggets staff.

Machine Learning 160

Machine Learning Data Science Python Data 160

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. I know that is an expensive statement to make😊 To be fair, I’m a big fan of data catalogs, or metadata management , to be precise.

Metadata 62

Metadata Data Warehouse ETL Tools Data Workflow 62

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Data Science

KDnuggets

DECEMBER 29, 2022

It's the end of the year, and so it's time for KDnuggets to assemble a team of experts and get to the bottom of what the most important data science, machine learning, AI and analytics developments of 2022 were.

Machine Learning 140

Machine Learning Data Science Data IT 140

The Modern Data Company

DECEMBER 29, 2022

Banking and Capital Markets are undergoing a period of transformation. The global economic outlook is somewhat fragile, but banks are in an excellent position to survive and thrive as long as they have the right tools in place. According to Deloitte’s report 2023 Banking and Capital Markets Outlook , banks must find ways to adapt to global disruption and understand the changing needs of consumers to find success.

Banking 52

Banking Pipeline-centric Building Finance 52

Monte Carlo

DECEMBER 29, 2022

No one wants to read marketing fluff, especially not data engineers. These builders and architects are prone to scoff at any article detailing concepts at a “high-level.” Everyone understands that data lineage and data pipeline monitoring are important, but the real question is, “how do you build it?” Caveat emptor, the following articles are for the technically inclined and definitely not for the faint of heart.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

DataKitchen

DECEMBER 29, 2022

The Terms and Conditions of a Data Contract are Automated Production Data Tests. A data contract is a formal agreement between two parties that defines the structure and format of data that will be exchanged between them. Data contracts are a new idea for data and analytic team development to ensure that data is transmitted accurately and consistently between different systems or teams.

Data Validation 52

Data Validation Data Data Integration SQL 52

Data Engineering Podcast

DECEMBER 29, 2022

Summary Making effective use of data requires proper context around the information that is being used. As the size and complexity of your organization increases the difficulty of ensuring that everyone has the necessary knowledge about how to get their work done scales exponentially. Wikis and intranets are a common way to attempt to solve this problem, but they are frequently ineffective.

Management 130

Management Metadata Business Intelligence Data Lake 130

Databand.ai

DECEMBER 29, 2022

The Top Data Strategy Influencers and Content Creators on LinkedIn Eitan Chazbani 2022-12-29 14:08:41 What’s the latest in the data world? In a space that moves at a rapid-fire pace, keeping up with new trends and evolving best practices can be dizzying. But having the right network can make all the difference. Regularly following updates from leaders in the data strategy space can go a long way toward not only helping you stay up to date on the latest and greatest, but also allowing you to join

BI 52

BI Consulting Data Science Data Governance 52

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

Engineering