Ascend.io

MAY 19, 2023

Moore in his book, Crossing the Chasm ) rush to build and launch hundreds of new tools to the market (Stage 2). In the data world, this disruption manifested in the form of cloud computing with technologies such as Redshift, Snowflake, and Spark. What is the post-modern data stack? Let’s review it briefly.

Data Pipeline 52

Data Pipeline Data Engineering Data Engineer Media 52

AltexSoft

OCTOBER 3, 2022

A triple is the most basic knowledge graph model you can build with two nodes and one edge explaining their connection. The logical basis of RDF is extended by related standards RDFS (RDF Schema) and OWL (Web Ontology Language). Knowledge graphs for building personal assistants and chatbots.

Relational Database 52

Relational Database Banking Media Computer Science 52

ProjectPro

NOVEMBER 22, 2021

The StructType and StructField classes in PySpark are used to define the schema to the DataFrame and create complex columns such as nested struct, array, and map columns. StructType is a collection of StructField objects that determines column name, column data type, field nullability, and metadata. appName('ProjectPro').getOrCreate()

Hadoop 52

Hadoop Python Datasets Metadata 52

dbt Developer Hub

NOVEMBER 28, 2021

We build a product based on the standards, conventions, and capabilities that are created there, and at least 70% of our engineering time is spent in contribution. This could just as easily have been Snowflake or Redshift, but I chose BigQuery because one of my data sources is already there as a public dataset.

Raw Data 52

Raw Data Metadata Database Datasets 52

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 70

Data Warehouse Cloud Kafka Cloud Storage 70

Netflix Tech

OCTOBER 27, 2020

Netflix Scheduler is built on top of Meson which is a general purpose workflow orchestration and scheduling framework to execute and manage the lifecycle of the data workflow. Bulldozer makes data warehouse tables more accessible to different microservices and reduces each individual team’s burden to build their own solutions.

Data Warehouse 97

Data Warehouse Datasets Data Big Data 97

Monte Carlo

JANUARY 25, 2023

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. We can specify the fields of the contract in addition to metadata like ownership, SLA, and where the table is located. Consistency in your tech stack.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

Zalando Engineering

SEPTEMBER 28, 2022

So the team decided to build a new tool to replace the old, overcome the feature and scalability related shortcomings, on top of this new architecture. Solution Design The first decision to make was whether to build a new CMS from scratch, or use an existing, third-party solution. The main entry is the landing page itself.

Certification 52

Certification Architecture Data Schemas Metadata 52

Towards Data Science

JANUARY 17, 2024

A Maven repository is a central place used for storing build artifacts like JAR files, libraries, and other dependencies that are used in Maven-based projects. spark.sql.catalog.spark_catalog: Sets the Spark catalog to Delta Lake’s catalog, allowing table management and metadata operations to be handled by Delta Lake.

Big Data 70

Big Data Data Data Storage SQL 70

Monte Carlo

MARCH 2, 2023

Otherwise you may produce more data anomalies than you prevent. Data Contracts Image courtesy of Andrew Jones. You can think of data contracts as circuit breakers, but for data schemas instead of the data itself. The answer?

Food 52

Food Data SQL Data Pipeline 52

ProjectPro

JANUARY 31, 2023

Why is HDFS only suitable for large data sets and not the correct tool for many small files? NameNode is often given a large space to contain metadata for large-scale files. The metadata should come from a single file for optimal space use and economic benefit. And storing these metadata in RAM will become problematic.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Monte Carlo

APRIL 20, 2023

I can surface ownership metadata and alert the relevant owners to make sure the appropriate changes are made so these breakages never happen. This way no decisions get made on bad data and our team becomes a proactive part of the solution,” said then Senior Director of Data at Freshly, Vitaly Lilich.

Data Warehouse 52

Data Warehouse BI Data Government 52

Cloudera

JANUARY 11, 2021

In addition, it can be challenging to keep a strong control of costs and to know where your data resides in an effort to serve your business well. Shared Data Experience (SDX), a shared persistent layer of access models, lineage-audit trace, and all metadata, is the key to the Cloudera data lake implementation.

Data Warehouse 62

Data Warehouse Pharmaceutical Data Lake BI 62

Towards Data Science

FEBRUARY 15, 2023

Delta Lake also refuses writes with wrongly formatted data (schema enforcement) and allows for schema evolution. It contains a detailed description of each operation performed, including all the metadata about the operation. show() The history object is a Spark Data Frame. delta_table.history().select("version",

Data Lake 77

Data Lake Data Warehouse Hadoop Data Architecture 77

Zalando Engineering

SEPTEMBER 8, 2021

We want to avoid unwanted data coupling and allow Renderers to be reused in other contexts with minimal risks. Renderers have access to Zalando’s GraphQL Mutation APIs which allows remote data to be modified. It only builds the Renderers that are shown on the current page. The page rendering always starts with an Entity.

Engineering 52

Engineering Computer Science Data Schemas Coding 52

Confluent

APRIL 30, 2019

When building a topology with the Processor API, you explicitly name each processing node in the topology, and also provide the name(s) of all of its parent nodes (the only exception are source nodes, which do not have any parents). .< build(properties); final KafkaStreams streams = new KafkaStreams(topology, properties); streams.

Kafka 89

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ProjectPro

APRIL 26, 2016

Pig vs Hive Criteria Pig Hive Type of Data Apache Pig is usually used for semi structured data. Used for Structured Data Schema Schema is optional. Hive requires a well-defined Schema. Language It is a procedural data flow language. Hive stores the metadata in RDBMS rather than HDFS.

Hadoop 40

Hadoop Metadata SQL Database 40

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

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