Engineering at Meta

FEBRUARY 7, 2023

This new data schema was born partly out of our cartographic tiling logic, and it includes everything necessary to make a map of the world. Daylight ensures that our maps are up-to-date and free of geometry errors, vandalism, and profanity.

Entertainment 138

Entertainment Transportation Data Schemas AWS 138

Workfall

SEPTEMBER 18, 2023

Pre-filter and pre-aggregate data at the source level to optimize the data pipeline’s efficiency. Adapt to Changing Data Schemas: Data sources aren’t static; they evolve. Account for potential changes in data schemas and structures.

Data Pipeline 93

Data Pipeline Raw Data Data Schemas Healthcare 93

Cloudyard

OCTOBER 23, 2023

The data’s structure frequently changes, with new columns or alterations introduced. Meeting this challenge requires the development of robust data pipelines capable of modifying table columns to align with the evolving source data schema.

Data Schemas 52

Data Schemas Data Pipeline Structured Data Architecture 52

DataKitchen

MAY 10, 2024

Have all the source files/data arrived on time? Is the source data of expected quality? Are there issues with data being late, truncated, or repeatedly the same? Have there been any unnoted changes to the data schema or format? I Did Not Get All The Data; I Only Got Part.

Data Ingestion 53

Data Ingestion Transportation High Quality Data Data Schemas 53

Grouparoo

JANUARY 30, 2022

release is our first major iteration on the user interface for creating your data pipeline. release, we added Models, which allowed data engineers to sync multiple data schemas to Destinations.

PostgreSQL 52

PostgreSQL MySQL Data Schemas SQL 52

ProjectPro

FEBRUARY 8, 2023

You can produce code, discover the data schema, and modify it. Smooth Integration with other AWS tools AWS Glue is relatively simple to integrate with data sources and targets like Amazon Kinesis, Amazon Redshift, Amazon S3, and Amazon MSK. AWS Glue automates several processes as well.

AWS 98

AWS Scala Metadata Data Lake 98

Data Engineering Podcast

APRIL 7, 2019

How does the concept of a data slice play into the overall architecture of your platform? How do you manage transformations of data schemas and formats as they traverse different slices in your platform? How does the concept of a data slice play into the overall architecture of your platform?

Data Pipeline 100

Data Pipeline Pipeline-centric Database-centric AWS 100

Netflix Tech

DECEMBER 14, 2018

A schemaless system appears less imposing for application developers that are producing the data, as it (a) spares them from the burden of planning and future-proofing the structure of their data and, (b) enables them to evolve data formats with ease and to their liking. This is depicted in Figure 1.

Media 96

Media Database Metadata Data Schemas 96

Grouparoo

OCTOBER 23, 2021

release of Grouparoo is a huge step forward for data engineers using Grouparoo to reliably sync a variety of types of data to operational tools. Models enable Grouparoo to work with multiple data schemas at once. Here are the key features of the release.

AWS 52

AWS Data Schemas Datasets Data Engineering 52

Monte Carlo

MARCH 28, 2024

“There were a couple of challenges because it’s easy to break this type of pipeline and an analyst would work for quite a while to find the data he’s looking for.” It involves a contract with the client sending the data, schema registry, and pipeline owners responsible for fixing any issues.

Engineering 75

Engineering Pipeline-centric BI Google Cloud 75

Cloudera

JANUARY 20, 2021

The training data-set represents sensor data of an office room and with this data, a model is built to predict if the room is occupied by a person or not. In the next few sections, we’ll talk about the training data schema, classification model, batch score table, and web application.

Machine Learning 115

Machine Learning Database Data Science Building 115

Rockset

MARCH 31, 2022

DAY 2 On day 2, as I was learning a data schema I had never seen before, I was able to write the SQL, with some amazing help from Rockset. I extracted a string value containing deeply nested JSON data with multiple arrays, subdocuments, sub arrays, etc.,

MongoDB 52

MongoDB Data Architect Data Schemas SQL 52

Cloudera

DECEMBER 21, 2023

Using the SQL AI Assistant, we can dramatically improve our work by having an intelligent SQL expert by our side, one that also knows our data schema very well. We can save time finding the right data, building the right syntax, and getting any new query started, with the generate feature.

SQL 67

SQL Data Warehouse Business Analyst Data Schemas 67

Snowflake

FEBRUARY 27, 2023

. “With this approach, Snowflake has not only helped us to break our data monolith, but also, and most importantly, to design microservices capable of publishing business events, which eliminates the risk of breaking pipelines when data schemas are modified, including with SaaS tools,” said Cormont.

Cloud 52

Cloud Retail Data Warehouse Data 52

Booking.com Engineering

DECEMBER 2, 2022

BigQuery also offers native support for nested and repeated data schema[4][5]. We take advantage of this feature in our ad bidding systems, maintaining consistent data views from our Account Specialists’ spreadsheets, to our Data Scientists’ notebooks, to our bidding system’s in-memory data.

Systems 52

Systems Cloud MySQL Relational Database 52

The Modern Data Company

MAY 8, 2023

And by leveraging distributed storage and open-source technologies, they offer a cost-effective solution for handling large data volumes. In other words, the data is stored in its raw, unprocessed form, and the structure is imposed when a user or an application queries the data for analysis or processing.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

And by leveraging distributed storage and open-source technologies, they offer a cost-effective solution for handling large data volumes. In other words, the data is stored in its raw, unprocessed form, and the structure is imposed when a user or an application queries the data for analysis or processing.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

And by leveraging distributed storage and open-source technologies, they offer a cost-effective solution for handling large data volumes. In other words, the data is stored in its raw, unprocessed form, and the structure is imposed when a user or an application queries the data for analysis or processing.

Data Management 52

Data Management Management Data Lake Data Governance 52

Engineering at Meta

OCTOBER 17, 2023

Deleting those GraphQL definitions makes it possible to delete business logic; deleting business logic makes it possible to delete data schema definitions, which in turn allows unused data to be deleted.

Coding 115

Coding Engineering Portfolio Data Schemas 115

Knowledge Hut

NOVEMBER 3, 2023

Skills Required for MongoDB for Data Science To excel in MongoDB for data science, you need a combination of technical and analytical skills: Database Querying: It is necessary to know how to write sophisticated queries using the query language of MongoDB. Quickly pull (fetch), filter, and reduce data.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Knowledge Hut

OCTOBER 4, 2023

It will ingest the data through Power BI and leverage the complete power of machine learning for easy collaboration. Support CDM: The CDM (Common Data Model) is a series of standardized data schema and a metasystem that enables data consistency and its application across business processes.

BI 52

BI Systems Raw Data Business Intelligence 52

AltexSoft

OCTOBER 3, 2022

The logical basis of RDF is extended by related standards RDFS (RDF Schema) and OWL (Web Ontology Language). They allow for representing various types of data and content (data schema, taxonomies, vocabularies, and metadata) and making them understandable for computing systems.

Relational Database 52

Relational Database Banking Media Computer Science 52

Rockset

AUGUST 18, 2020

This means new data schemas, new sources and new types of queries pop up every few days. Developers need to test and iterate on new features - Your product roadmap is constantly evolving based on what your users need, and your developers want to personalize, experiment and A/B test quickly.

Data Lake 40

Data Lake Data Schemas BI Kafka 40

Tweag

FEBRUARY 22, 2023

Scattering configuration data, schemas and knowledge across many different tools, written in many different languages (HCL, YAML, JSON, TOML, Puppet, Ansible, Helm, etc.) YAML has been pronounced dead for the last 10 years or so, and unfortunately, here it stands. But something is in the air. isn’t sustainable.

Management 52

Management Programming Language Data Schemas Programming 52

Towards Data Science

MARCH 9, 2023

Now that the cluster is created and the data is in order we can start the notebook by creating it on the same top-left menu used for the cluster and table setup. link] Time to meet the MLLib.

Machine Learning 74

Machine Learning Building Datasets Big Data 74

Monte Carlo

JUNE 26, 2023

After launching our partnership with Databricks last year, Monte Carlo has aggressively expanded our native Databricks and Apache Spark™ integrations to extend data observability into the Delta Lake and Unity Catalog, and in the process, drive even more value for Databricks customers.

Data Lake 52

Data Lake Metadata Bytes Machine Learning 52

Cloudera

JULY 26, 2021

Auditabily: Data security and compliance constituents need to understand how data changes, where it originates from and how data consumers interact with it.

Generalist 119

Generalist Telecommunication Healthcare Data Science 119

Knowledge Hut

MARCH 19, 2024

Mirror production data schemas: While masking sensitive information, reflecting production data shapes, interfaces and dependencies reduces surprises when changes reach customers. Implement role-based access controls: Grant developers, testers and ops team members only the minimum permissions needed for their duties.

Pipeline-centric 52

Pipeline-centric Database-centric Software Engineer Software Engineering 52

Monte Carlo

MAY 31, 2022

“There were a couple of challenges because it’s easy to break this type of pipeline and an analyst would work for quite a while to find the data he’s looking for.” It involves a contract with the client sending the data , schema registry, and pipeline owners responsible for fixing any issues.

BI 52

BI Data Warehouse Unstructured Data Data Schemas 52

Striim

SEPTEMBER 11, 2024

Strimmer: To build the data pipeline for our Strimmer service, we’ll use Striim’s streaming ETL data processing capabilities, allowing us to clean and format the data before it’s stored in the data store.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Monte Carlo

AUGUST 2, 2022

Moreover, Monte Carlo’s security-first approach to data observability ensures that data never leaves your Databricks Lakehouse Platform. Monte Carlo can automatically monitor and alert for data schema, volume, freshness, and distribution anomalies within the Databricks Lakehouse Platform.

Building 52

Building Data Lake Business Intelligence Data Pipeline 52

Knowledge Hut

DECEMBER 28, 2023

They must understand SEO terms like meta data, schema, indexing and more. Search Engine Optimization Search Engine Optimization (SEO) improves website visibility and ranking on search engine result pages. Web developers need to ensure that the website is built with SEO guidelines in mind.

Programming Language 52

Programming Language Python Certification MongoDB 52

Monte Carlo

OCTOBER 11, 2022

Unbeknownst to you, the training data contains a table with aggregated visitor website data with columns that haven’t been updated in a month. It turns out the marketing operations team upgraded to Google Analytics 4 to get ahead of the July 2023 deadline which changed the data schema.

IT 52

IT Datasets Data Warehouse Data Analysis 52

Monte Carlo

OCTOBER 17, 2022

Join their standups, understand the unique way they interact with data, and use the experience to abstract the process and tooling you’ll be providing to other teams. This could include FAQs, custom tooling, common libraries or data schemas. This helps determine what you need as part of your standard “migration kit.”

Data Warehouse 59

Data Warehouse AWS MySQL Data 59

Databand.ai

JULY 19, 2023

The data pipeline should be designed to handle the volume, variety, and velocity of the data. This includes choosing the right data storage and processing technologies, designing the data schema, and planning the data transformations.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Netflix Tech

OCTOBER 27, 2020

As the paved path for moving data to key-value stores, Bulldozer provides a scalable and efficient no-code solution. Users only need to specify the data source and the destination cluster information in a YAML file. Bulldozer provides the functionality to auto-generate the data schema which is defined in a protobuf file.

Data Warehouse 99

Data Warehouse Datasets Data Big Data 99

Monte Carlo

JUNE 28, 2022

Monte Carlo can automatically monitor and alert for data schema, volume, freshness, and distribution anomalies within the data lake environment. Delta Lake The Delta Lake is an open source storage layer that sits on top of and imbues an existing data lake with additional features that make it more akin to a data warehouse.

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52