Tweag

MAY 16, 2023

To minimize the risk of misconfigurations, Nickel features (opt-in) static typing and contracts, a powerful and extensible data validation framework. For configuration data, we tend to use contracts. Contracts are a principled way of writing and applying runtime data validators.

MySQL 131

MySQL Metadata Data Validation Coding 131

Airbnb Tech

NOVEMBER 28, 2023

To fully enable this incentivization approach, we believed it would be paramount to introduce the concept of a data quality score directly tied to data assets. We identified the following objectives for the score: Evolve our understanding of data quality beyond a simple binary definition (certified vs uncertified).

Data Warehouse 98

Data Warehouse Metadata Data Certification 98

Towards Data Science

MAY 11, 2023

Lookup time for set and dict is more efficient than that for list and tuple , given that sets and dictionaries use hash function to determine any particular piece of data is right away, without a search. The existence of data schema at a class level makes it easy to discover the expected data shape.

Programming 90

Programming Python Data Schemas Java 90

Databand.ai

JULY 3, 2023

The value of that trust is why more and more companies are introducing Chief Data Officers – with the number doubling among the top publicly traded companies between 2019 and 2021, according to PwC. In this article: Why is data reliability important? Note that data validity is sometimes considered a part of data reliability.

Data Validation 52

Data Validation Data Collection Data Machine Learning 52

Rock the JVM

FEBRUARY 5, 2024

By Riccardo Cardin In this article, we delve into the concept of type classes in Kotlin, a powerful tool that allows developers to abstract logic for different data types. We’ll take data validation as an example to show how type classes can be used to write generic and reusable code. withType (). required ( "userId" ), amount.

Portfolio 74

Portfolio Scala Data Validation Coding 74

RandomTrees

FEBRUARY 2, 2024

DataGPT helps businesses to effectively analyze their data by providing important information and in-depth data exploration. Benefits of DataGPT Save Time: DataGPT saves the time of analysts by addressing queries. Generate Code: DataGPT creates code for data pipelines and schema definition.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Pipeline 52

Ascend.io

JUNE 8, 2023

Data Stewardship Every company — even departments within a company — has different definitions for even the most common data elements within different datasets. These varying definitions are based on the format, function, origin, and different uses for the data in practice.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Databand.ai

AUGUST 30, 2023

Data Quality Rules Data quality rules are predefined criteria that your data must meet to ensure its accuracy, completeness, consistency, and reliability. These rules are essential for maintaining high-quality data and can be enforced using data validation, transformation, or cleansing processes.

Data Cleanse 52

Data Cleanse Metadata High Quality Data Datasets 52

Monte Carlo

MARCH 12, 2024

As you add new data sources to your data stores, Dataplex leverages the structured and unstructured metadata with built-in data quality checks to maintain integrity. Implement Custom SQL Rules Dataplex supports several custom SQL rules for data quality checks as well.

Google Cloud 52

Google Cloud Metadata SQL Data Lake 52

Monte Carlo

MAY 26, 2023

Data Validation : Like a tuning fork ensuring our instruments are at the right pitch, data validation checks that incoming data meets certain criteria, catching data consistency issues before they enter our system. Looker also has a semantic layer called LookML.

Datasets 52

Datasets Data Warehouse Data Validation Data 52

Data Engineering Weekly

FEBRUARY 12, 2023

It’s true Big Data is dead, but we can’t deny it is a result of collective advancement in data processing techniques. link] Dropbox: Balancing quality and coverage with our data validation framework Data Testing should be part of the data creation lifecycle; it is not a standalone process.

Data Engineering 52

Data Engineering Data Engineer Engineering Hadoop 52

Knowledge Hut

JUNE 30, 2023

It helps in data consistency and accuracy by maintaining a standardized representation of data across the system. Data Definition Language (DDL) The Data Definition Language is a set of predefined commands or statements that are used to define and also manage the defined structure and organization of a designated database.

MySQL 52

MySQL Medical Relational Database Healthcare 52

Ascend.io

JULY 19, 2023

Establish clear data governance policies. The policies should outline rules and standards for data. These should be explicit and prescriptive, addressing the 5 aspects below: Domain and business key definitions: Clearly define your business keys and the domains they belong to. Develop a data product lifecycle framework.

Data Governance 40

Data Governance Government Metadata Data 40

Airbnb Tech

NOVEMBER 24, 2020

This was recognized as a key opportunity to define a consistent “gold standard” for data quality at Airbnb. A Multi-dimensional Challenge While all stakeholders agreed that data quality was important, employee definitions of “data quality” encompassed a constellation of different issues.

Data Warehouse 52

Data Warehouse Certification Data Pipeline Data 52

DataKitchen

APRIL 13, 2021

Because it is such a new category, both overly narrow and overly broad definitions of DataOps abound. Observe, optimize, and scale enterprise data pipelines. . Validio — Automated real-time data validation and quality monitoring. . We ensure your team is the first to know and the first to solve. .

Consulting 120

Consulting Machine Learning Data Science Data Pipeline 120

dbt Developer Hub

SEPTEMBER 28, 2022

User_Id Location Role Level Zone 123 California Editor AAA 1 427 Utah Participant ABA 1 864 Georgia Admin CCC 3 A data engineer working off of a “build list” will add a filter for WHERE Role = 'Participant'. During the data validation step, the analyst would discover that there is actually a third Role of Editor that no one was aware of.

Engineering 52

Engineering Raw Data Datasets BI 52

Cloudera

AUGUST 31, 2021

These schemas will be created based on its definitions in existing legacy data warehouses. Smart DwH Mover helps in accelerating data warehouse migration. Smart Data Validator helps in extensive data reconciliation and testing. Smart Query Convertor converts queries and views to be made compatible on CDW.

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

Grouparoo

OCTOBER 6, 2021

Tianhui Michael Li The Three Rs of Data Engineering by Tobias Macey Data testing and quality Automate Your Pipeline Tests by Tom White Data Quality for Data Engineers by Katharine Jarmul Data Validation Is More Than Summary Statistics by Emily Riederer The Six Words That Will Destroy Your Career by Bartosz Mikulski Your Data Tests Failed!

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Advancing Analytics: Data Engineering

JUNE 21, 2019

As a general rule, you don’t want your cloud systems strongly tied to your on-premises systems – if there is some bad data in your extract, you need to be able to deal with it without going back to the source system. We deliberately build loosely-coupled data processing systems to build independence from source.

Data Warehouse 52

Data Warehouse Business Intelligence Data Data Validation 52

Monte Carlo

JANUARY 25, 2023

That being said, it tends to be much easier to reprocess data in the data warehouse when we do find bad records, whereas that might not be possible in a streaming environment. Definition of data contracts Similar to contracts in production services, contracts in the warehouse should be implemented in code and version controlled.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

Grouparoo

NOVEMBER 29, 2021

Alternatively, this can be data generated by another process and then made available for subsequent processing. Therefore, the source data may be raw, unfiltered, and unrefined, or polished and fully formed. In this article, we'll look at the definition of data sources and their general types. What is a Data Source?

Raw Data 40

Raw Data Big Data Relational Database Data Warehouse 40

ProjectPro

FEBRUARY 16, 2023

Data engineers use SQL to modify any database and table structure and extract subsets of the data from the database for various business analytics use cases. For example, the data manipulation language (DML) and data definition language (DDL) allow engineers to collect and manipulate data scripts and design and modify data structures.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

U-Next

JULY 1, 2022

Data validation can be practised both on the client and server sides to reduce the XSS negative effects. . There’s definitely going to be a lot of pressure on you, but it’s about time you show your skills and potential. Cross-site scripting, also known as XSS vulnerability, is a client-side code injection attack.

Transportation 52

Transportation Engineering Systems Data Validation 52

Knowledge Hut

APRIL 19, 2023

Web Development vs Programming [Head-to-Head Comparison] Here's a comparison table highlighting the key difference between programming and web development: Parameter Programming Web Development Definition The process of writing, testing, and maintaining computer programs using a programming language.

Programming 59

Programming Programming Language Java Coding 59

phData: Data Engineering

JANUARY 3, 2022

Software Engineering principles apply to the complete data product lifecycle. This allows us to create new versions of our data sets, populate them with data, validate our data, and then redeploy our views on top of that data to use the new version of our data.

IT 52

IT AWS Software Engineer Software Engineering 52

dbt Developer Hub

MAY 2, 2022

they fall short when it comes to data validation and general developer ergonomics (IMO) and that’s where pydantic comes in; among other things, pydantic implements a validator decorator that is used to define custom validations for model fields (e.g., dbt-cloud handles the request boilerplate (e.g., CLI arguments).

Cloud 52

Cloud Metadata Python Database 52

AltexSoft

NOVEMBER 23, 2021

Dynamic data catalog — to organize data by profiling, tagging, classifying, and mapping it to business definitions so that end-users could easily find what they need. Data quality control — to ensure that all information is correct by applying data validation logic.

Process 69

Process Data Lake Metadata Data Warehouse 69

Knowledge Hut

APRIL 20, 2023

Data Governance Examples Here are some examples of data governance in practice: Data quality control: Data governance involves implementing processes for ensuring that data is accurate, complete, and consistent. This may involve data validation, data cleansing, and data enrichment activities.

Data Governance 59

Data Governance Government Data Cleanse Data Security 59

ProjectPro

JUNE 2, 2021

Exploratory Data Analysis (EDA) is best described as an approach to find patterns, spot anomalies or differences, and other features that best summarise the main characteristics of a data set. However, it is important to remember that Exploratory Data Analysis is barely a set of techniques, steps, or rules; rather it is anything but.

Data Analysis 52

Data Analysis Python Machine Learning Data Science 52

ProjectPro

JUNE 18, 2015

Enterprises that completely crowdsource data to make critical business decisions, definitely does have some loopholes. Table of Contents Big Data Analytics + Crowdsourcing = A Happy Couple Crowdsourcing Big Data How crowdsourcing helps ease the process of big data analytics?

Big Data 52

Big Data Process Data Cleanse Data Analytics 52

ProjectPro

NOVEMBER 30, 2021

If you are into Data Science or Big Data, you must be familiar with an ETL pipeline. This guide provides definitions, a step-by-step tutorial, and a few best practices to help you understand ETL pipelines and how they differ from data pipelines. If not, then don't worry.

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

AUGUST 21, 2015

The 3 core methods of a reducer are – 1)setup () – This method of the reducer is used for configuring various parameters like the input data size, distributed cache, heap size, etc. Function Definition- public void setup (context) 2)reduce () it is heart of the reducer which is called once per key with the associated reduce task.

Hadoop 40

Hadoop Big Data Metadata Java 40