Simon Späti

MAY 26, 2023

Welcome to the third and final installment of our series “Data Modeling: The Unsung Hero of Data Engineering.” If you’ve journeyed with us from Part 1, where we dove into the importance and history of data modeling, or joined us in Part 2 to explore various approaches and techniques, I’m delighted you’ve stuck around. In this third part, we’ll delve into data architecture patterns and their influence on data modeling.

Architecture 130

Architecture Data Engineering Data Engineer Engineering 130

Monte Carlo

MAY 26, 2023

What is data freshness and why is it important? Data freshness, sometimes referred to as data timeliness, is the frequency in which data is updated for consumption. It is an important dimension of data quality and a pillar of data observability because recently refreshed data is more accurate, and thus more valuable. Since it is impractical and expensive to have all data refreshed on a near real-time basis, data engineers ingest and process most analytical data in batches with pipelines designed

Data Pipeline 98

Data Pipeline Data Data Warehouse Machine Learning 98

Simon Späti

MAY 26, 2023

Welcome to the third and final installment of our series “Data Modeling: The Unsung Hero of Data Engineering.” If you’ve journeyed with us from Part 1, where we dove into the importance and history of data modeling, or joined us in Part 2 to explore various approaches and techniques, I’m delighted you’ve stuck around. In this third part, we’ll delve into data architecture patterns and their influence on data modeling.

Architecture 130

Architecture Data Engineering Data Engineer Engineering 130

KDnuggets

MAY 26, 2023

ChatGPT might have some loophole to provide unreliable facts.

151

151

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

databricks

MAY 26, 2023

The Asian Employee Network (AEN) launched two years ago, during Lunar New Year 2021. AEN was created with the objective of building a.

Building 83

Building 83

KDnuggets

MAY 26, 2023

An LLM Trained on 1T Tokens of Text and Code by MosaicML Foundation Series.

Coding 110

Coding Process 110

Hevo

MAY 26, 2023

As a data engineer, you hold all the cards to make data easily accessible to your business teams. Your team just requested a MongoDB to Databricks connection on priority. We know you don’t wanna keep your data scientists and business analysts waiting to get critical business insights.

MongoDB 52

MongoDB Business Analyst Data Engineering Data Engineer 52

Monte Carlo

MAY 26, 2023

Imagine an orchestra, where each instrument represents a different data source in your system. The violins could be your customer database, the cellos your transaction records, the trumpets your web analytics, and so on. When all the instruments play in tune and in time, following the same musical score, the result is a harmonious symphony – a rich, coherent piece of music that conveys a clear theme and emotion.

Datasets 52

Datasets Data Warehouse Data Validation Data 52

Ripple Engineering

MAY 26, 2023

Decentralized blockchains such as the XRP Ledger (XRPL) rely on the collective decision-making of their participants in order to coordinate changes to the protocol. Amendments are the primary mechanism for initiating changes to the XRPL, which track changes to transaction processing. This includes new features, enhancements to existing functionality, and bug fixes.

Coding 52

Coding Process Designing Accessible 52

Cloudyard

MAY 26, 2023

Read Time: 1 Minute, 40 Second Consider a scenario when business wants to clean up the database for a particular requirement. Clean up here we mean drop all the tables lies inside the database. At first glance it seems pretty straightforward and we can issue the DROP table command to remove all the tables. But Business has put one condition here that if any table is part of VIEW then no need to drop the table.

Database 52

Database Coding Process IT 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

Confluent

MAY 26, 2023

Meet Sharmey Shah—Area Vice President in Sales. Find out how she’s made a difference at Confluent in the year since she’s joined.

57

57

Towards Data Science

MAY 26, 2023

Spend less time debugging your pipelines by using Hamilton ’s out of the box lineage capabilities. Hamilton + Lineage: Enabling you to visualize and understand how things connect. This was created using driver.visualize_path_between(). Image by author. Hamilton is a general purpose open-source micro-framework for describing dataflows. It is great for data & Machine Learning (ML) work.

Metadata 85

Metadata Data Science Coding Machine Learning 85

Confluent

MAY 26, 2023

To remain competitive, BigCommerce migrated to Confluent for real-time analytics and insights and to perform ETL processes.

Data 57

Data Process 57