Data Engineering Weekly

JANUARY 12, 2025

Generative AI demands the processing of vast amounts of diverse, unstructured data (e.g., meeting recordings and videos), which contrasts with traditional SQL-centric systems for structured data. The fundamental shift from traditional SQL-centric to AI-centric data processing further widened the efficiency gap.

Pipeline-centric 57

Pipeline-centric Data Engineering Data Engineer Engineering 57

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

Engineering at Meta

MARCH 18, 2024

Users can query using regular expressions on log lines, arbitrary metadata fields attached to logs, and across log files of hosts and services. Logarithm’s data model Logarithm represents logs as a named log stream of (host-local) time-ordered sequences of immutable unstructured text, corresponding to a single log file. in PyTorch).

Engineering 94

Engineering Metadata Architecture Designing 94

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 120

Metadata Coding Building Project 120

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

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore). Tables are governed as per agreed upon company standards.

Big Data 78

Big Data Data Management Management Metadata 78

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

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

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

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 74

Cloud Building Amazon Web Services Metadata 74

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 97

Media Database Metadata Data Schemas 97

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

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

RandomTrees

SEPTEMBER 17, 2024

The Unity Catalog is Databricks governance solution which integrates with Databricks workspaces and provides a centralized platform for managing metadata, data access, and security. Improved Data Discovery The tagging and documentation features in Unity Catalog facilitate better data discovery.

Data Governance 52

Data Governance Government Metadata Machine Learning 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.

Data Warehouse 81

Data Warehouse Unstructured Data Pharmaceutical MySQL 81

phData: Data Engineering

SEPTEMBER 19, 2023

Want to learn more about data governance? Check out our Data Governance on Snowflake blog! Metadata Management Data modeling methodologies help in managing metadata within the data lake. Metadata describes the characteristics, attributes, and context of the data.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

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

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

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 98

Engineering Raw Data Data Science Machine Learning 98

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

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

Sync Computing

NOVEMBER 7, 2024

Despite these limitations, data warehouses, introduced in the late 1980s based on ideas developed even earlier, remain in widespread use today for certain business intelligence and data analysis applications. While data warehouses are still in use, they are limited in use-cases as they only support structured data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Unstructured Data 52

Cloudera

NOVEMBER 15, 2024

With flexible schema and partitioning, Iceberg tables can scale to handle petabytes of data while compressing logs to save on storage costs. The metadata-driven approach ensures quick query planning so defenders don’t have to deal with slow processes when they need fast answers.

Metadata 59

Metadata Unstructured Data Data Lake Government 59

Netflix Tech

OCTOBER 27, 2020

The field names should exactly match for Bulldozer to convert the structured data entries into the key-value pairs. Users can use the protobuf schema KeyMessage and ValueMessage to deserialize data from Key-Value DAL as well. In this case, profile_id field is the key while email and age fields are included in the value schema.

Data Warehouse 100

Data Warehouse Datasets Data Big Data 100

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

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

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 97

Bytes Google Cloud Cloud Storage Utilities 97

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

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

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 56

Management Metadata Software Engineer Software Engineering 56

Confluent

AUGUST 29, 2019

Instead of storing tables and columns, Neo4j represents all data as a graph, meaning that the data is a set of nodes with labels and relationships. Nodes are like our data entities (in this example, we use Person ). This approach to structuring data is called the property graph model.

Kafka 55

Kafka Process Algorithm Cloud 55

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

Rockset

FEBRUARY 21, 2019

Which is a great reason for Rockset to support SQL queries on PDF files, in our mission to make data more usable to everyone. Now add PDFs to the mix, and users can combine PDF data with data of other formats, from various sources, into their SQL analyses. . from the document along with the text.

SQL 52

SQL Metadata Structured Data IT 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

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 Data Warehouse Unstructured Data Government 52

ProjectPro

OCTOBER 15, 2014

Hive- Performance Benchmarking Hive vs Pig Pig vs Hive - Differences Pig Hive Procedural Data Flow Language Declarative SQLish Language For Programming For creating reports Mainly used by Researchers and Programmers Mainly used by Data Analysts Operates on the client side of a cluster. Does not have a dedicated metadata database.

Hadoop 52

Hadoop Java Unstructured Data SQL 52

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