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

Snowflake

MAY 23, 2024

Processing complex, schema-less, semistructured, hierarchical data can be extremely time-consuming, costly and error-prone, particularly if the data source has polymorphic attributes. For many data sources, the schema of the data source can change without warning.

Data Pipeline 99

Data Pipeline Raw Data Data Schemas Technology 99

Snowflake

OCTOBER 22, 2024

Rather than scrubbing or redacting sensitive fields — or worse, creating rules to generate “realistic” data from the ground up —you simply point our app at your production schema, train one of the included models, and generate as much synthetic data as you like. It’s basically an “easy button” for synthetic data.

Data 93

Data Data Schemas Datasets Machine Learning 93

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

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 Metadata Scala Data Lake 98

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

Confluent

SEPTEMBER 27, 2019

Today, nearly everyone uses standard data formats like Avro, JSON, and Protobuf to define how they will communicate information between services within an organization, either synchronously through RPC calls or asynchronously through Apache Kafka ® messages.

Kafka 16

Kafka Data Governance Bytes Government 16

Confluent

JUNE 13, 2019

The data from these detections are then serialized into Avro binary format. The Avro alert data schemas for ZTF are defined in JSON documents and are published to GitHub for scientists to use when deserializing data upon receipt.

Kafka 102

Kafka Bytes Data Pipeline Python 102

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

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 98

Machine Learning Building Datasets Big Data 98

Snowflake

AUGUST 28, 2024

Data integration As a Snowflake Native App, AI Decisioning leverages the existing data within an organization’s AI Data Cloud, including customer behaviors and product and offer details. During a one-time setup, your data owner maps your existing data schemas within the UI, which fuels AI Decisioning’s models.

Cloud 63

Cloud Insurance Data Schemas Algorithm 63

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

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 107

Coding Engineering Portfolio Data Schemas 107

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 56

Data Ingestion Transportation High Quality Data Data Schemas 56

Cloudyard

JANUARY 21, 2025

Conclusion Schema evolution is a vital feature that allows data pipelines to remain flexible and resilient as data structures change over time. Whether dealing with CSV, Parquet, or JSON data, schema evolution ensures that your data processing workflows continue to function smoothly, even when new columns are added or removed.

Data Schemas 59

Data Schemas Data Pipeline Data Warehouse Data Storage 59

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

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

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

Confluent

MAY 28, 2019

Therefore, not restricting access to the Schema Registry might allow an unauthorized user to mess with the service in such a way that client applications can no longer be served schemas to deserialize their data. Allow end user REST API calls to Schema Registry over HTTPS instead of the default HTTP.

Management 85

Management Kafka Java Certification 85

Netflix Tech

OCTOBER 23, 2019

While matplotlib integration is quite standard among notebooks, Polynote also has native support for data exploration?—?including including a data schema view, table inspector, plot constructor and Vega support. Polynote integrates with two of the most popular open source visualization libraries, Vega and Matplotlib.

Scala 93

Scala Machine Learning Python Coding 93

Towards Data Science

FEBRUARY 15, 2023

Delta Lake also refuses writes with wrongly formatted data (schema enforcement) and allows for schema evolution. Delta Lake also works with the concept of ACID transactions, that is, no partial writing caused by job failures or inconsistent readings.

Data Lake 98

Data Lake Data Warehouse Hadoop Architecture 98

Engineering at Meta

DECEMBER 19, 2024

Therefore: Glean doesnt decide for you what data you can store. Indeed, most languages that Glean indexes have their own data schema and Glean can store arbitrary non-programming-language data too. The data is ultimately stored using RocksDB , providing good scalability and efficient retrieval.

Coding 74

Coding Programming Language SQL Programming 74

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 SQL Data Schemas 52

Snowflake

AUGUST 25, 2023

Snowflake is leveraging our SQL expertise to provide the best text-to-SQL capabilities that combine syntactically correct SQL with a deep understanding of customers’ sophisticated data schemas, governed and protected by their existing rights, roles and access controls.

Coding 88

Coding SQL Data Cleanse Database 88

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

Towards Data Science

JANUARY 17, 2024

One of its neat features is the ability to store data in a compressed format, with snappy compression being the go-to choice. Another cool aspect of Parquet is its flexible approach to data schemas. This adaptability makes it super user-friendly for evolving data projects.

Big Data 97

Big Data Data Data Storage SQL 97

Pinterest Engineering

MAY 2, 2023

Traditionally, product engineers need to be exposed to the infra complexity, including data schema, resource provisions, and storage allocations, which involves multiple teams.

Lambda Architecture 90

Lambda Architecture Datasets Software Engineer Software Engineering 90

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

Cloudera

FEBRUARY 9, 2021

Schema Management. Avro format messages are stored in Kafka for better performance and schema evolution. Cloudera Schema Registry is designed to store and manage data schemas across services. NiFi data flows can refer to the schemas in the Registry instead of hard coding. . > Minutes.

Data Warehouse 72

Data Warehouse Cloud Kafka Cloud Storage 72

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

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

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

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 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 Management Data Lake Data Governance 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 Machine Learning 52