Coding, Definition, Metadata and Software Engineering

How to get started with dbt

Christophe Blefari

MARCH 1, 2023

dbt is a development framework that combines modular SQL with software engineering best practices to make data transformation reliable, fast, and fun. You can also add metadata on models (in YAML). a macro — a macro is a Jinja function that either do something or return SQL or partial SQL code.

Data Warehouse

Data Warehouse SQL Metadata Raw Data

Pioneering Data Observability:Data, Code, Infrastructure, & AI

Towards Data Science

AUGUST 8, 2023

Pioneering Data Observability: Data, Code, Infrastructure, & AI The four dimensions of data observability: data, code, infrastructure, and ai? Unreliable data doesn’t live in a silo… it’s impacted by all three ingredients of the data ecosystem: data + code + infrastructure. You look at the code.

Coding

Coding Data Software Engineer Software Engineering

Pioneering Data Observability: Data, Code, Infrastructure, & AI

Monte Carlo

AUGUST 7, 2023

Prevention: Finally, data observability also provides mechanisms to prevent data issues from happening in the first place, like placing circuit breaking in pipelines and creating visibility around the impact code changes would make on data, among other proactive measures of preventing bad data from entering your pipelines in the first place.

Coding

Coding Data Software Engineer Software Engineering

Webinars

Generative AI Deep Dive: Advancing from Proof of Concept to Production

Understanding User Needs and Satisfying Them

Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Leading the Development of Profitable and Sustainable Products

How To Get Promoted In Product Management

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Announcing Nickel 1.0

Tweag

MAY 16, 2023

The manifest of a web app, the configuration of an Apache virtual host, an Infrastructure-as-Code (IaC) cloud deployment (Terraform, Kubernetes, etc.). Configuration is more often than not considered a second-class engineering discipline, like a side activity of software engineering.

MySQL

MySQL Metadata Data Validation Coding

Data Observability Out Of The Box With Metaplane

Data Engineering Podcast

JANUARY 7, 2022

In this episode Metaplane founder Kevin Hu shares his working definition of the term and explains the work that he and his team are doing to cut down on the time to adoption for this new set of practices. Today’s episode is Sponsored by Prophecy.io – the low-code data engineering platform for the cloud.

BI

BI Data Warehouse Metadata SQL

The Future of Data Engineering as a Data Engineer

Monte Carlo

JANUARY 23, 2024

Every team has their own analytic domain they own, forcing decentralized team structures around broadly standardized definitions of what “good” data looks like. If people don’t agree on what they call things in the data warehouse or what the definition of a metric is, then this lack of consensus will be reflected downstream.

Data Engineering

Data Engineering Data Engineer Engineering Data

Scalable Strategies For Protecting Data Privacy In Your Shared Data Sets

Data Engineering Podcast

FEBRUARY 6, 2022

Today’s episode is Sponsored by Prophecy.io – the low-code data engineering platform for the cloud. Now all the data users can use software engineering best practices – git, tests and continuous deployment with a simple to use visual designer. How does it work? How does it work?

Data Pipeline

Data Pipeline Data Metadata Software Engineer

Ready or Not. The Post Modern Data Stack Is Coming.

Monte Carlo

MARCH 28, 2023

Monte Carlo joined the fray and said, “Maybe having engineers manually code unit tests isn’t the best way to ensure data quality.” Today, data engineers continue to stomp on hard coded pipelines and on-premises servers as they march up the modern data stack slope of enlightenment.

Data Warehouse

Data Warehouse Raw Data Data Pipeline Software Engineer

The Rise of the Data Engineer

Maxime Beauchemin

JANUARY 20, 2017

Like data scientists, data engineers write code. Unlike data scientists — and inspired by our more mature parent, software engineering — data engineers build tools, infrastructure, frameworks, and services. It’s also fairly common for engineers to develop and manage their own job orchestrator/scheduler.

Data Engineering

Data Engineering Data Engineer Engineering ETL Tools

Data Contracts and Data Observability: Whatnot’s Full Circle Journey to Data Trust

Monte Carlo

JANUARY 4, 2024

And like any new — and admittedly abstract — concept, there are several different definitions of data contracts floating around on LinkedIn , Medium , and Substack. The idea here is that whichever code base an engineer is working in, they’re going through the same general flow in each place,” says Zach.

Data

Data Metadata Software Engineer Software Engineering

What is Data Observability? 5 Key Pillars To Know

Monte Carlo

AUGUST 10, 2023

The five pillars My data observability definition has not changed since I first coined it in 2019: Data observability refers to an organization’s comprehensive understanding of the health and performance of the data within their systems. We have updated this post to reflect this rapidly maturing space. What is Data observability?

Data Pipeline

Data Pipeline Software Engineer Software Engineering Machine Learning

Zero-ETL, ChatGPT, And The Future of Data Engineering

Towards Data Science

APRIL 3, 2023

Monte Carlo joined the fray and said, “Maybe having engineers manually code unit tests isn’t the best way to ensure data quality.” Today, data engineers continue to stomp on hard coded pipelines and on-premises servers as they march up the modern data stack slope of enlightenment.

Data Engineering

Data Engineering Data Engineer Engineering Data Warehouse

The Complete Front-End Developer Roadmap 2024

Knowledge Hut

DECEMBER 29, 2023

A Front-End Developer is a type of Software Engineer who works on front-end development. For example, let us look at the code snippet below. <!DOCTYPE The “head” tags (<head> and </head>) contain the metadata or information about the website. code files and assets.

Portfolio

Portfolio Amazon Web Services Programming Language Coding

Optimizing NixOS Search

Tweag

DECEMBER 12, 2022

It also provides metadata information such as descriptions, maintainers, and compatible platforms. Currently, search.nixos.org imports flake metadata through custom nix code that wraps flake evaluations. Metadata For Export nix flake show reads in the file flake.nix which provides an interface to artifacts like packages.

Metadata

Metadata Programming Software Engineer Software Engineering

October 2021 dbt Update: Metrics and Hat Tricks ?

dbt Developer Hub

OCTOBER 14, 2021

dbt will support metric definitions ? With this feature, you'll be able to centrally define rules for aggregating metrics (think, "active users" or "MRR") in version controlled, tested, documented dbt project code. Hex just launched an integration with dbt! Get started here. Things to Watch ? What's missing? Spreadsheets?

Metadata

Metadata BI Software Engineer Software Engineering

How Best Egg Implemented a Reliable Data Mesh with Data Observability

Monte Carlo

MARCH 16, 2023

Randy’s team also uses custom code to ingest specific types of third-party data, like their bank processor’s EBCDICfiles. Randy’s advice is to stay flexible and remember that business users, software engineers, and platform engineers all have their own jobs and priorities.

Software Engineer

Software Engineer Software Engineering Data Governance Government

What Is Data Pipeline Automation?

Ascend.io

MARCH 17, 2023

These engineering functions are almost exclusively concerned with data pipelines, spanning ingestion, transformation, orchestration, and observation — all the way to data product delivery to the business tools and downstream applications. In fact, it’s been a recurring theme in software engineering.

Data Pipeline

Data Pipeline Datasets Data Software Engineer

What Is Data Pipeline Automation?

Ascend.io

MARCH 17, 2023

These engineering functions are almost exclusively concerned with data pipelines, spanning ingestion, transformation, orchestration, and observation — all the way to data product delivery to the business tools and downstream applications. In fact, it’s been a recurring theme in software engineering.

Data Pipeline

Data Pipeline Datasets Data Software Engineer

How to Work With PDF in Python

Knowledge Hut

MAY 3, 2024

PDFMiner allows the user to analyze text data and obtain the definite location of a text. PDFQuery A light Python wrapper that uses minimum code to extract data from PDFs. The code for extracting the document information from the PDF— # get_doc_info.py The code for rotating the article is as follows— # rotate_pages.py

Python

Python Digital Media Coding Programming

Functional Python, Part III: The Ghost in the Machine

Tweag

MAY 24, 2023

In this final episode, I’ll cover testing strategies that can be learnt from functional programming and applied to your Python code. I, Test It’s hardly a revelation that testing the code we write — and automating that process — is an essential element of software engineering practice. mappend ( b ) ). mappend ( c ) == a.

Python

Python Programming Language Programming Coding

Orchestrating Data/ML Workflows at Scale With Netflix Maestro

Netflix Tech

OCTOBER 18, 2022

We want users to rely on shared templates and reuse their workflow definitions across their team, saving time and effort on creating the same functionality. It serves thousands of users, including data scientists, data engineers, machine learning engineers, software engineers, content producers, and business analysts, for various use cases.

Java

Java Data Machine Learning Systems

97 things every data engineer should know

Grouparoo

OCTOBER 6, 2021

This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams. For example, grouping the ones about metadata, discoverability, and column naming might have made a lot of sense.

Data Engineering

Data Engineering Data Engineer Engineering Pipeline-centric

How Best Egg Implemented a Reliable Data Mesh with Data Observability

Monte Carlo

MARCH 16, 2023

Randy’s team also uses custom code to ingest specific types of third-party data, like their bank processor’s EBCDICfiles. Randy’s advice is to stay flexible and remember that business users, software engineers, and platform engineers all have their own jobs and priorities.

Software Engineer

Software Engineer Software Engineering Data Governance Government

Improving Stream Data Quality with Protobuf Schema Validation

Confluent

FEBRUARY 22, 2019

This led us towards choosing a format that supports defining a schema in a programming language agnostic Interface Definition Language (IDL) which could then propagate the schema across to all the applications that need to work on that data. The metadata consists of Protobuf custom options. Protobuf Rules That We Decided to Enforce.

Kafka

Kafka Programming Language Metadata Data

Operational Analytics: What every software engineer should know about low-latency queries on large data sets

Rockset

JULY 25, 2019

Definition of Operational Analytics Processing An operational analytics system helps you make instant decisions from reams of real-time data. You collect new data from your data sources and they all stream into your operational data engine. This is another form of operational analytics. to the write and then persists it in the LOG.

Software Engineer

Software Engineer Software Engineering Engineering PostgreSQL

Is Modern Data Warehouse Architecture Broken?

Monte Carlo

APRIL 16, 2022

Modular code and dramatically reduced runtimes made the ETL model radically less painful…so much so the use of popular transformation tools expanded downstream from data engineers to data consumers such as data scientists and analysts. As data engineers, we need to emphasize data usability in addition to data quality.

Data Warehouse

Data Warehouse Architecture Data Government

Implementing Data Contracts in the Data Warehouse

Monte Carlo

JANUARY 25, 2023

Definition of data contracts Similar to contracts in production services, contracts in the warehouse should be implemented in code and version controlled. All of these options allow you to define the schema of the contract, describe the data, and store relevant metadata like semantics, ownership, and constraints.

Data Warehouse

Data Warehouse Data High Quality Data Metadata

Schemas, Contracts, and Compatibility

Confluent

MAY 21, 2019

Note that the same definitions of fields and types that once defined the REST API are now part of the event schema. They are at the intersection of the way we develop software, the way we manage data, metadata and the interactions between teams. If they didn’t, they would be caught during code review. Couldn’t you tell?”

Kafka

Kafka Insurance Architecture Database

Growth Engineering at Netflix?—?Automated Imagery Generation

Netflix Tech

FEBRUARY 9, 2021

Ensure the titles are appropriate for a broad audience, which means all titles need to be tagged with metadata. First, the fields can be coded by hand. To accomplish this, the Asset Management Service needs to translate an asset group into a rule definition for the Customization Service. Localized images for each of the titles.

Engineering

Engineering Entertainment Metadata Designing

Building CI/CD with Airflow, GitLab and Terraform in GCP

Ripple Engineering

FEBRUARY 2, 2021

The Ripple Data Engineering team is expanding, which means higher frequency changes to our data pipeline source code. This means we need to build better, more configurable and more collaborative tooling that prevents code collisions and enforces software engineering best practices. py}" -.gitlab-ci.yml

Building

Building Python Google Cloud Coding

Experimentation is a major focus of Data Science across Netflix

Netflix Tech

JANUARY 11, 2022

We use Metaflow to pair existing infrastructure for metric definitions and data collection from our Experimentation Platform with custom analysis methods that are based on a difference-in-difference approach. without having to become software engineers themselves.

Data Science

Data Science Data Algorithm Engineering

Kafka Streams’ Take on Watermarks and Triggers

Confluent

MARCH 20, 2019

Important: If you’re using Suppress.untilWindowClose , you should definitely also set the grace period on the window definition, since the default is 24 hours (for legacy reasons). This follows from the definition of a final result. John is a software engineer at Confluent, focusing mainly on Kafka Streams.

Kafka

Kafka Programming Process Designing

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

AltexSoft

MARCH 14, 2023

Software engineers use a technology stack — a combination of programming languages, frameworks, libraries, etc. — While the open-source part is definitely a good thing, it requires a high level of expertise as there’s often no GUI. This means that companies don’t necessarily need a large data engineering team.

IT

IT Data Warehouse Data Governance Data Lake

Best Practices for Android Developer Productivity

Zalando Engineering

JULY 27, 2016

The efficiency of your software engineering work depends not only on your deep knowledge and expertise, but also on the toolset, proper environment configuration, and team collaboration activities. Use these metadata annotations to decorate your code to help catch bugs and define code rules.

Metadata

Metadata Coding Java Project

61 Data Observability Use Cases From Real Data Teams

Monte Carlo

MAY 17, 2023

Flag System Authorization And Integration Failures Mitigate Risk of Code Failures 10. Upstream Code Impacting Data Systems 14. Data observability platforms deploy features such as data lineage, query change detection, and correlation insights to determine where issues are occurring at the system, code, or data level.

Data

Data Data Pipeline Data Engineering Data Engineer

61 Data Observability Use Cases That Aren’t Totally Made Up

Monte Carlo

MAY 17, 2023

Flag System Authorization And Integration Failures Mitigate Risk of Code Failures 10. Upstream Code Impacting Data Systems 14. Data observability platforms deploy features such as data lineage, query change detection, and correlation insights to determine where issues are occurring at the system, code, or data level.

Data Pipeline

Data Pipeline Data Data Engineering Data Engineer

The Ultimate Modern Data Stack Migration Guide

phData: Data Engineering

JULY 18, 2023

Key Benefits and Features of Using dbt Version Control With Git: SQL code is stored within git and version-controlled. Modernization and Optimization With this migration strategy, an organization will make significant modifications to its existing data warehouse architecture, design, and code during the migration process.

Data Warehouse

Data Warehouse Pipeline-centric Government Data

50 Artificial Intelligence Interview Questions and Answers [2023]

ProjectPro

OCTOBER 20, 2021

The benefit of AutoML is that it is a low-code or no-code approach, wherein folks who do not have experience in Machine Learning can also implement it. This will help non-coding folks achieve the state of the art performance with minimal coding effort. GitHub is the go-to website for source code management.

Machine Learning

Machine Learning Algorithm Government Data Science

What is a Data Mesh — and How Not to Mesh it Up

Monte Carlo

JULY 30, 2020

Much in the same way that software engineering teams transitioned from monolithic applications to microservice architectures , the data mesh is, in many ways, the data platform version of microservices. What is a data mesh? It does not have the same emphasis on decentralization and domain driven architecture as data mesh.

IT

IT Data Lake Business Intelligence Data Architecture

How to get started with dbt

Pioneering Data Observability:Data, Code, Infrastructure, & AI

Webinars

Trending Sources

Pioneering Data Observability: Data, Code, Infrastructure, & AI

Webinars

Announcing Nickel 1.0

Data Observability Out Of The Box With Metaplane

The Future of Data Engineering as a Data Engineer

Scalable Strategies For Protecting Data Privacy In Your Shared Data Sets

Ready or Not. The Post Modern Data Stack Is Coming.

The Rise of the Data Engineer

Data Contracts and Data Observability: Whatnot’s Full Circle Journey to Data Trust

What is Data Observability? 5 Key Pillars To Know

Zero-ETL, ChatGPT, And The Future of Data Engineering

The Complete Front-End Developer Roadmap 2024

Optimizing NixOS Search

October 2021 dbt Update: Metrics and Hat Tricks ?

How Best Egg Implemented a Reliable Data Mesh with Data Observability

What Is Data Pipeline Automation?

What Is Data Pipeline Automation?

How to Work With PDF in Python

Functional Python, Part III: The Ghost in the Machine

Orchestrating Data/ML Workflows at Scale With Netflix Maestro

97 things every data engineer should know

How Best Egg Implemented a Reliable Data Mesh with Data Observability

Improving Stream Data Quality with Protobuf Schema Validation

Operational Analytics: What every software engineer should know about low-latency queries on large data sets

Is Modern Data Warehouse Architecture Broken?

Implementing Data Contracts in the Data Warehouse

Schemas, Contracts, and Compatibility

Growth Engineering at Netflix?—?Automated Imagery Generation

Building CI/CD with Airflow, GitLab and Terraform in GCP

Experimentation is a major focus of Data Science across Netflix

Kafka Streams’ Take on Watermarks and Triggers

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

Best Practices for Android Developer Productivity

61 Data Observability Use Cases From Real Data Teams

61 Data Observability Use Cases That Aren’t Totally Made Up

The Ultimate Modern Data Stack Migration Guide

50 Artificial Intelligence Interview Questions and Answers [2023]

What is a Data Mesh — and How Not to Mesh it Up

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