Monte Carlo

JUNE 26, 2023

Over the last several years, Databricks has given users the ability to add more structure to the data inside their data lake. Monte Carlo can automatically monitor and alert for data schema, volume, freshness, and distribution anomalies within the data lake environment.

Data Lake 52

Data Lake Metadata Bytes Machine Learning 52

Netflix Tech

DECEMBER 14, 2018

A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve. NMDB is built to be a highly scalable, multi-tenant, media metadata system that can serve a high volume of write/read throughput as well as support near real-time queries.

Media 96

Media Database Metadata Data Schemas 96

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. The main player in the context of the first data lakes was Hadoop, a distributed file system, with MapReduce, a processing paradigm built over the idea of minimal data movement and high parallelism.

Data Lake 76

Data Lake Data Warehouse Hadoop Architecture 76

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.

Food 52

Food Data SQL Data Pipeline 52

phData: Data Engineering

SEPTEMBER 27, 2024

Here’s how a composable CDP might incorporate the modeling approaches we’ve discussed: Data Storage and Processing : This is your foundation. You might choose a cloud data warehouse like the Snowflake AI Data Cloud or BigQuery. It’s like turning your data warehouse into a data distribution center.

Data 52

Data Raw Data Data Lake Architecture 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 Relational Database AWS 52

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

Hadoop Big Data Metadata Java 40

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. Hcatalog can be used to share data structures with external systems.

Hadoop 40

Hadoop Metadata SQL Database 40

Cloudera

JANUARY 11, 2021

How self-service data warehousing frees IT resources. Cloudera Data Warehouse (CDW) is a cloud service and an integral part of the newly released Cloudera Data Platform (CDP). Key features are: Highly scalable and performant open-source engines for BI and data warehousing workloads. Simplified provisioning.

Data Warehouse 63

Data Warehouse Pharmaceutical Data Lake BI 63

Towards Data Science

NOVEMBER 4, 2023

Often it is a data warehouse solution (DWH) in the central part of our infrastructure. Data warehouse exmaple. What I like about it is that it makes it really easy to work with various data file formats, i.e. SQL, XML, XLS, CSV and JSON. It will be a great tool for those with minimal Python knowledge.

Data Engineering 81

Data Engineering Data Engineer Engineering BI 81

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. And over time, we’ve invested effort into cleaning up our lineages, simplifying our logic,” said SeatGeek Director of Data Engineering, Brian London. Data lineage can help!

Data Warehouse 52

Data Warehouse BI Data Government 52