Snowflake

AUGUST 25, 2023

The future of SQL, LLMs and the Data Cloud Snowflake has long been committed to the SQL language. SQL is the primary access path to structured data, and we believe it is critical that LLMs are able to interoperate with structured data in a variety of ways.

Coding 73

Coding SQL Data Cleanse Database 73

Monte Carlo

FEBRUARY 26, 2024

Metaphor takes a modern approach to metadata by creating a social environment for data consumption, from the use of social hashtags in the data, social posts to share information, to automating a live wiki to access documentation.

Metadata 52

Metadata Government Data Data Governance 52

Towards Data Science

JANUARY 17, 2024

These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction. They are designed to handle the challenges of big data like size, speed, and structure. Data engineers often face a plethora of choices.

Big Data 72

Big Data Data Data Storage SQL 72

Rockset

SEPTEMBER 20, 2022

Embedded content: [link] NFT and Crypto Price Analysis Although blockchain data is open for anyone to see, it can be difficult to make that on-chain data consumable for analysis. Each individual smart contract can have a different data schema, making data aggregation challenging when analyzing hundreds or even thousands of contracts.

PostgreSQL 52

PostgreSQL MongoDB SQL Datasets 52

Towards Data Science

FEBRUARY 15, 2023

Before going into further details on Delta Lake, we need to remember the concept of Data Lake, so let’s travel through some history. Delta Lake also refuses writes with wrongly formatted data (schema enforcement) and allows for schema evolution.

Data Lake 80

Data Lake Data Warehouse Hadoop Data Architecture 80

ProjectPro

NOVEMBER 22, 2021

show(truncate=False) #Drop duplicates on selected columns dropDisDF = df.dropDuplicates(["department","salary"]) print("Distinct count of department salary : "+str(dropDisDF.count())) dropDisDF.show(truncate=False) } Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Q6.

Hadoop 52

Hadoop Python Datasets Metadata 52

Monte Carlo

JANUARY 25, 2023

The contracts themselves should be created using well-established protocols for serializing and deserializing structured data such as Google’s Protocol Buffers (protobuf), Apache Avro, or even JSON. In those cases, we try to test on a blank or sample of data. The most important reason to choose one over the other?

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

ProjectPro

JANUARY 31, 2023

Data Variety Hadoop stores structured, semi-structured and unstructured data. RDBMS stores structured data. Data storage Hadoop stores large data sets. RDBMS stores the average amount of data. Works with only structured data. It also discusses several kinds of data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

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. Follows SQL Dialect and is a declarative language.

Hadoop 40

Hadoop Metadata SQL Database 40

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. a technology choice such as Spark Streaming is overly focused on throughput at the expense of latency) or data formats (e.g.,

Generalist 114

Generalist Telecommunication Healthcare Data Science 114

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. What is Big Data?

Hadoop 40

Hadoop Big Data Metadata Java 40

Netflix Tech

DECEMBER 14, 2018

data access semantics that guarantee repeatable data read behavior for client applications. System Requirements Support for Structured Data The growth of NoSQL databases has broadly been accompanied with the trend of data “schemalessness” (e.g., key value stores generally allow storing any data under a key).

Media 94

Media Database Metadata Data Schemas 94

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 97

Data Warehouse Datasets Data Big Data 97

Confluent

JUNE 13, 2019

For alert rates of millions per night, scientists need a more structured data format for automated analysis pipelines. After researching formats—and reading about Confluent’s suggestion of using Avro with Kafka —we settled on using Avro, an open source, JSON-based binary format, for serializing the data in the alert messages.

Kafka 102

Kafka Bytes Data Pipeline Python 102

Netflix Tech

OCTOBER 31, 2018

The curious reader might have noticed that a majority of these characteristics relate to properties of the data managed by NMDB. Specifically, structured data that is modeled around the notion of a media timeline, with additional spatial properties. called “ N etflix M edia D ata B ase” (NMDB) that is used to address them.

Media 54

Media Metadata Data MongoDB 54