phData: Data Engineering

SEPTEMBER 19, 2023

This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake? What are Data Modeling Methodologies, and Why Are They Important for a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Data Engineering Podcast

JUNE 17, 2021

Kirk Marple has spent years working with data systems and the media industry, which inspired him to build a platform for automatically organizing your unstructured assets to make them more valuable. The data you’re looking for is already in your data warehouse and BI tools. No more scripts, just SQL.

Unstructured Data 100

Unstructured Data Data Warehouse Metadata Media 100

Engineering at Meta

FEBRUARY 6, 2024

DotSlash handles transparently fetching, decompressing, and verifying the appropriate remote artifact for the current operating system and CPU. Our continuous integration (CI) system supports special configuration for DotSlash jobs where a user must specify: A set of builds to run (these can span multiple platforms).

Metadata 117

Metadata Coding Building Project 117

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

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Architecture 124

Architecture Metadata Government Kafka 124

AltexSoft

AUGUST 22, 2022

A data fabric is an architecture design presented as an integration and orchestration layer built on top of multiple disjointed data sources like relational databases , data warehouses , data lakes, data marts , IoT , legacy systems, etc., to provide a unified view of all enterprise data.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

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

Our Incident Playbooks cover emergency procedures to initiate in case a certain set of conditions is met, for example when one of our systems is overloaded and the existing resiliency measures (e.g. When the bigger system context is considered, there are more options available to mitigate issues. processing of price updates).

Management 57

Management Metadata Software Engineer Software Engineering 57

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

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 110

IT Unstructured Data Data Architecture Government 110

AltexSoft

JUNE 7, 2021

You don’t need to archive or clean data before loading. The system automatically replicates information to prevent data loss in the case of a node failure. To understand how the entire mechanism works, we need to get familiar with Hadoop structure and key parts. A file stored in the system ?an’t fail-safety.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Data Engineering Podcast

JULY 1, 2018

Preamble Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline you’ll need somewhere to deploy it, so check out Linode. When doing data collection from various sources, how do you ensure that intellectual property rights are respected?

Metadata 100

Metadata Machine Learning Data Preparation Data Collection 100

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc. Sensor data.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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

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

This operational component places some cognitive load on our engineers, requiring them to develop deep understanding of telemetry and alerting systems, capacity provisioning process, security and reliability best practices, and a vast amount of informal knowledge about the cloud infrastructure.

Cloud 73

Cloud Building Amazon Web Services Metadata 73

ProjectPro

JANUARY 31, 2023

Key features Hadoop RDBMS Overview Hadoop is an open-source software collection that links several computers to solve problems requiring large quantities of data and processing. RDBMS is a part of system software used to create and manage databases based on the relational model. RDBMS stores structured data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Data Engineering Weekly

MARCH 24, 2023

Data creation is often the differentiator between the success & the failure of a data team. A business process or workflow engine is a software system that enables businesses to execute well-defined steps to complete a user’s intention. Event Sourcing Change Data Capture [CDC] Outbox pattern 1.

Engineering 67

Engineering Data Transportation Database 67

Monte Carlo

NOVEMBER 20, 2023

Data quality can be impacted by all sorts of events and errors within a pipeline or ingestion source—from distribution anomalies caused by a keying error to the natural entropy that exists within a complex data system. Your data will grow. Errors can be human, technical, or a mix of both. Your platform will expand.

Government 69

Government Data Data Governance Datasets 69

Snowflake

MARCH 30, 2023

For this reason, a new data management for ML framework has emerged to help manage this complexity: the “feature store.” Feature store As described in Tecton’s blog , a feature store is a data management system for managing ML feature pipelines, including the management of feature engineering code and data.

Engineering 83

Engineering Raw Data Data Science Scala 83

AltexSoft

JUNE 26, 2023

It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more. Data integration , on the other hand, happens later in the data management flow. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Cloudera

SEPTEMBER 17, 2020

By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. .

Unstructured Data 81

Unstructured Data Data Warehouse Pharmaceutical MySQL 81

Rockset

DECEMBER 17, 2021

Here’s the final architecture: I’ve been doing some flavour of systems integration for the past 15 years, and usually I finish a project and think “it shouldn’t have taken that much effort”. For those unfamiliar, DynamoDB makes database scalability a breeze, but with some major caveats.

SQL 52

SQL NoSQL Database Design Metadata 52

Rockset

AUGUST 2, 2023

For one, the company decided to invest in an API Insights Lab where customers and partners across suppliers, carriers, governments and insurance companies could use maritime data as part of their internal systems and workflows. They used MongoDB as their metadata store to capture vessel and company data.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

ProjectPro

AUGUST 11, 2021

Data Lake vs Data Warehouse - The Differences Before we closely analyse some of the key differences between a data lake and a data warehouse, it is important to have an in depth understanding of what a data warehouse and data lake is. Data Lake vs Data Warehouse - The Introduction What is a Data warehouse?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 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 69

Bytes Google Cloud Cloud Storage Utilities 69

AltexSoft

JULY 18, 2023

Spark SQL brings native support for SQL to Spark and streamlines the process of querying semistructured and structured data. Many industries, from telecommunications to finance and healthcare, use Spark to run ELT and ETL (Extract, Transform, Load) operations, where vast amounts of data are prepared for further analysis.

Big Data 52

Big Data Data Process Process Hadoop 52

Striim

JANUARY 4, 2023

The dashboard users may assume that data is being transformed the same way as when the service was initially launched. Similarly, an engineer might change something in the schema of the source system. Data contracts tackle this uncertainty and end assumptions by creating a formal agreement. What are data contracts?

PostgreSQL 52

PostgreSQL Data Warehouse Data Lake Data 52

Netflix Tech

DECEMBER 14, 2018

In the previous blog posts in this series, we introduced the N etflix M edia D ata B ase ( NMDB ) and its salient “Media Document” data model. In this post we will provide details of the NMDB system architecture beginning with the system requirements?—?these key value stores generally allow storing any data under a key).

Media 94

Media Database Metadata Data Schemas 94

Silectis

JANUARY 3, 2021

” Artificial Intelligence AI is a broad term used to describe engineered systems that have been taught to do a task that typically requires human intelligence. BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

JULY 29, 2022

A Hadoop cluster is a group of computers called nodes that act as a single centralized system working on the same task. a client or edge node serves as a gateway between a Hadoop cluster and outer systems and applications. It loads data and grabs the results of the processing staying outside the master-slave hierarchy.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Ascend.io

JULY 19, 2023

Process: Building Robust Systems from Data Governance to Product Publishing Just as a well-oiled machine needs precise processes, a successful data mesh needs to establish and adhere to processes regarding data governance, data curation, and data product publishing. Implement a publishing approval process.

Data Governance 40

Data Governance Government Metadata Data 40

Ascend.io

AUGUST 31, 2023

Modern Cloud Data Platforms The native capabilities of the cloud providers have been joined by third-party services to offload that data into separate less costly systems that are optimized for analysis of that data. Transform before Load: The ETL process conforms data to the static, predefined warehouse schema.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Knowledge Hut

DECEMBER 21, 2023

Top 10 Hadoop Tools This Hadoop tools list will give you a brief idea about the top 10 Hadoop tools used by big data analysts. HDFS HDFS is the abbreviated form of Hadoop Distributed File System and is a component of Apache Hadoop. Before we understand what HDFS is, we first need to know what a file system is.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Hepta Analytics

FEBRUARY 14, 2022

The multiple databases will be queried, then passed through the transformation server to transform the data to comply with the business rule then the transformed the data is stored in a data store. This is also used for legacy systems. This means that your data store has to have capabilities of transforming the data.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

AltexSoft

SEPTEMBER 23, 2021

The larger the company, the more data it has to generate actionable insights. Because it is scattered across disparate systems, hardly available for analytical apps. Evidently, common storage solutions fail to provide a unified data view and meet the needs of companies for seamless data flow. Data lake vs data hub.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52