Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Ascend.io

FEBRUARY 28, 2024

Read More: AI Data Platform: Key Requirements for Fueling AI Initiatives How Data Engineering Enables AI Data engineering is the backbone of AI’s potential to transform industries , offering the essential infrastructure that powers AI algorithms.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Engineering at Meta

FEBRUARY 6, 2024

The script we use to generate DotSlash files injects metadata about the build job that makes it straightforward to trace the provenance of the underlying artifacts. The following is a hypothetical example of a generated DotSlash file for the CodeCompose LSP built from source at a specific commit in clang-opt mode.

Metadata 119

Metadata Coding Building Project 119

Monte Carlo

FEBRUARY 12, 2024

To differentiate and expand the usefulness of these models, organizations must augment them with first-party data – typically via a process called RAG (retrieval augmented generation). Today, this first-party data mostly lives in two types of data repositories.

Database 72

Database Unstructured Data Data Pipeline Metadata 72

AltexSoft

AUGUST 22, 2022

The self-service functionally allows the entire organization to find relevant data faster and gain valuable insights. Support for different data types and use cases. A data fabric supports structured, unstructured, and semi-structured data whether it comes in real-time or generated in batches. Data catalog.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Systems 87

Systems Hadoop Metadata Telecommunication 87

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

FEBRUARY 26, 2024

A data catalog is a constantly updated inventory of the universe of data assets within an organization. It uses metadata to create a picture of the data, as well as the relationships between data assets of diverse sources, and the processing that takes place as data moves through systems.

Metadata 52

Metadata Government Data Data Governance 52

ProjectPro

FEBRUARY 16, 2023

Data integration with ETL has evolved from structured data stores with high computing costs to natural state storage with read operation alterations thanks to the agility of the cloud. Data integration with ETL has changed in the last three decades. AWS Glue has a central metadata repository called the Glue catalog.

AWS 52

AWS Data Management ETL Tools Management 52

AltexSoft

NOVEMBER 10, 2021

In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes. At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Data Engineering Podcast

JULY 1, 2018

When doing data collection from various sources, how do you ensure that intellectual property rights are respected? How do you determine the taxonomies to be used for structuring data sets that are collected, labeled or enriched for your customers? What kinds of metadata do you track and how is that recorded/transmitted?

Metadata 100

Metadata Machine Learning Data Preparation Data Collection 100

Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 112

IT Unstructured Data Data Architecture Government 112

Snowflake

JULY 10, 2023

Processing files in a Python UDF and Stored Procedure has piqued the interest of our data scientists and paves the way for automation of new, complex data pipelines.” Mike Tuck, Air Pollution Specialist Why unstructured data?

Unstructured Data 40

Unstructured Data Python Process Scala 40

Zalando Engineering

JANUARY 30, 2023

Managing structured data in markdown is not ideal, despite the ability to use front matter for metadata. During the application review process it's indicated per application (from certain criticality tier onward) whether there are any playbooks defined for it and whether any of these are expired.

Management 55

Management Metadata Software Engineer Software Engineering 55

AltexSoft

JUNE 7, 2021

HDFS master-slave structure. A HDFS Master Node, called a NameNode , keeps metadata with critical information about system files (like their names, locations, number of data blocks in the file, etc.) and keeps track of storage capacity, a volume of data being transferred, etc. Data management and monitoring options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Netflix Tech

MARCH 5, 2019

Challenges & Opportunities in the Infra Data Space Security Events Platform for Anomaly Detection How can we develop a complex event processing system to ingest semi-structured data predicated on schema contracts from hundreds of sources and transform it into event streams of structured data for downstream analysis?

Cloud 73

Cloud Building Amazon Web Services Metadata 73

Cloudera

JUNE 25, 2021

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. Understanding the data sets to be replicated from the CDH Cluster.

Cloud 73

Cloud Data Lake Cloud Storage Metadata 73

Data Engineering Podcast

FEBRUARY 3, 2019

Open Context is an open access data publishing service for archaeology. It started because we need better ways of dissminating structured data and digital media than is possible with conventional articles, books and reports. What are your protocols for determining which data sets you will work with?

Digital Media 100

Digital Media Media PostgreSQL Datasets 100

ProjectPro

JANUARY 24, 2023

You can leverage AWS Glue to discover, transform, and prepare your data for analytics. In addition to databases running on AWS, Glue can automatically find structured and semi-structured data kept in your data lake on Amazon S3, data warehouse on Amazon Redshift, and other storage locations.

AWS 52

AWS ETL Tools Data Lake Scala 52

Monte Carlo

APRIL 1, 2021

Data Catalogs Can Drown in a Data Lake Although exceptionally flexible and scalable, data lakes lack the organization necessary to facilitate proper metadata management and data governance. Data discovery tools and platforms can help. Image courtesy of Adrian on Unsplash.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Monte Carlo

JULY 13, 2023

Utilizing a data permissions scanner and posture manager ensures that data engineers are informed about who has the potential to access data, which helps mitigate this risk. Automated processes scan all data stores and discover data, including semi-structured data such as JSON on a continual basis.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Hepta Analytics

FEBRUARY 14, 2022

Disadvantages of a data lake are: Can easily become a data swamp data has no versioning Same data with incompatible schemas is a problem without versioning Has no metadata associated It is difficult to join the data Data warehouse stores processed data, mostly structured data.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

RandomTrees

SEPTEMBER 6, 2020

A combination of structured and semi structured data can be used for analysis and loaded into the cloud database without the need of transforming into a fixed relational scheme first. This stage handles all the aspects of data storage like organization, file size, structure, compression, metadata, statistics.

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

Cloudera

MAY 17, 2021

Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform. Beyond there being a number of choices each with very different strengths, the parameters for your decision have also changed.

Data Warehouse 90

Data Warehouse Cloud Government Metadata 90

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

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Cloudera

SEPTEMBER 17, 2020

They were not able to quickly and easily query and analyze huge amounts of data as required. They also needed to combine text or other unstructured data with structured data and visualize the results in the same dashboards. Events or time-series data served by our real-time events or time-series data store solutions.

Unstructured Data 81

Unstructured Data Data Warehouse Pharmaceutical MySQL 81

Rockset

APRIL 26, 2023

These vector search queries are written to find similarities between products, while filtering both real-time metadata, like product availability, and historical metadata, like a user’s previous purchases. This will simplify your architecture considerably, deliver low-latency recommendation results, and enable metadata filtering.

Architecture 52

Architecture Transportation Data Lake Insurance 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. Hardware Hadoop uses commodity hardware.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Rockset

DECEMBER 17, 2021

For those unfamiliar, DynamoDB makes database scalability a breeze, but with some major caveats.

SQL 52

SQL NoSQL Database Design Metadata 52

Snowflake

MARCH 30, 2023

Automation , because the same loader patterns are used for both and the same metadata tags are expected from both, meaning the applied date timestamp in the business vault will match up with the raw date timestamp where it came from. These methods can be applied to structured and semi-structured data as well.

Engineering 84

Engineering Raw Data Data Science Machine Learning 84

Silectis

JANUARY 3, 2021

Data Architecture Data architecture is a composition of models, rules, and standards for all data systems and interactions between them. Data Catalog An organized inventory of data assets relying on metadata to help with data management. Database A collection of structured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. The difference between data warehouses, lakes, and marts.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 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

MARCH 5, 2024

The storage system is using Capacitor, a proprietary columnar storage format by Google for semi-structured data and the file system underneath is Colossus, the distributed file system by Google. depending on location) BigQuery maintains a lot of valuable metadata about tables, columns and partitions.

Bytes 69

Bytes Google Cloud Cloud Storage Utilities 69

Striim

JANUARY 4, 2023

This means that your contract should include metadata about your schema, which you can use to describe your data and add value constraints for certain fields (e.g., Ensure data contracts don’t affect iteration speed for software developers. Apache Avro) to serialize and deserialize structured data. temperature).

PostgreSQL 52

PostgreSQL Data Warehouse Data Data Lake 52