Data Engineering Podcast

FEBRUARY 27, 2022

If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription TimescaleDB, from your friends at Timescale, is the leading open-source relational database with support for time-series data. Time-series data is relentless and requires a database like TimescaleDB with speed and petabyte-scale.

Designing 100

Designing Metadata Data Lake Relational Database 100

Snowflake

MARCH 29, 2023

But even without the catalog, Iceberg Tables are still accessible if the user directly points at appropriate file locations. Iceberg supports many catalog implementations: Hive, AWS Glue, Hadoop, Nessie, Dell ECS, any relational database via JDBC, REST, and now Snowflake. © 2023 Snowflake Inc. All rights reserved.

Metadata 96

Metadata Scala Hadoop Relational Database 96

Data Engineering Weekly

MARCH 24, 2023

Data engineering starts to add value to the business by capturing events at each step of the business process. The events are then further enriched and analyzed to bring visibility to business operations. Event Sourcing Change Data Capture [CDC] Outbox pattern 1. However, Event sourcing comes with a few major limitations.

Engineering 67

Engineering Data Transportation Database 67

Knowledge Hut

JANUARY 3, 2024

In S3, data consists of the following components – key (name), value (data), version ID, metadata and access control lists. Amazon RDS Amazon Relational Database Service (RDS) facilitates the launching and managing of relational databases on the AWS platform.

AWS 52

AWS Amazon Web Services Certification Relational Database 52

Knowledge Hut

DECEMBER 19, 2023

These languages aid users in accessing the site or app that has been developed. It allows the addition of metadata to the changes, which facilitates team members in pinpointing the changes introduced in the code, why it was made, and when and who made it. This part is accessed by the users through the front-end application.

Java 98

Java Programming Language Architecture Database 98

AltexSoft

JUNE 7, 2021

Hadoop hides away the complexities of distributed computing, offering an abstracted API to get direct access to the system’s functionality and its benefits — such as. 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.)

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

AltexSoft

DECEMBER 23, 2022

ELT makes it easier to manage and access all this information by allowing both raw and cleaned data to be loaded and stored for further analysis. There’s a data science team that needs access to raw data for machine learning projects. This is the process of adding external data or context (metadata) to the existing data.

Process 52

Process Building Raw Data Data Lake 52

Netflix Tech

DECEMBER 14, 2018

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. under varying load conditions as well as a wide variety of access patterns; (b) scalability?—?persisting

Media 94

Media Database Metadata Data Schemas 94

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., Unified data access. What is data fabric? Data fabric architecture example.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

ProjectPro

NOVEMBER 15, 2021

When any particular project is open-sourced, it makes the source code accessible to anyone. Support for stream and batch processing, comprehensive state management, event-time processing semantics, and consistency guarantee for the state are just a few of Flink's capabilities.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

OCTOBER 28, 2015

The major difference between Sqoop and Flume is that Sqoop is used for loading data from relational databases into HDFS while Flume is used to capture a stream of moving data. The data sources can refer to databases, machine data, web APIs, relational databases, flat files, log files, and RSS (RDF Site Summary) feeds, to name a few.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

AUGUST 11, 2021

The data warehouse layer consists of the relational database management system (RDBMS) that contains the cleaned data and the metadata, which is data about the data. The RDBMS can either be directly accessed from the data warehouse layer or stored in data marts designed for specific enterprise departments.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

AltexSoft

JUNE 26, 2023

The ultimate goal of data integration is to gather all valuable information in one place, ensuring its integrity , quality, accessibility throughout the company, and readiness for BI, statistical data analysis, or machine learning. Most modern platforms expose public or private APIs as a way to access their data directly.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

SEPTEMBER 23, 2021

A data hub serves as a single point of access for all data consumers, whether it be an application, a data scientist, or a business user. The structure of data is usually predefined before it is loaded into a warehouse, since the DW is a relational database that uses a single data model for everything it stores.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

ProjectPro

NOVEMBER 22, 2021

PySpark runs a completely compatible Python instance on the Spark driver (where the task was launched) while maintaining access to the Scala-based Spark cluster access. StructType is a collection of StructField objects that determines column name, column data type, field nullability, and metadata. sports activities).

Hadoop 52

Hadoop Python Datasets Metadata 52

AltexSoft

JULY 19, 2022

There have been relational databases, data warehouses, data lakes, and even a combination of the latter two. The architectural shift means connecting data through a distributed mesh of data products accessed through standardized protocols instead of collecting data in monolithic warehouses and lakes.

Architecture 52

Architecture Data Lake Medical Datasets 52

AltexSoft

OCTOBER 8, 2021

At the same time, you get rid of the “data silos” problem: When no team or department has a unified view of all data due to fragments being locked in separate databases with limited access. Sensitive data can be protected using a combination of access controls and encryption. Data profiling and cleansing. Pre-built connectors.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

AltexSoft

SEPTEMBER 21, 2023

Accessible via a unified API, these new features enhance search relevance and are available on Elastic Cloud. Analysis of logs, metrics, and security events. Fields in these documents are defined and governed by mappings akin to a schema in a relational database. Real-time behavior modeling with ML.

Engineering 52

Engineering NoSQL Programming Language Java 52

ProjectPro

JUNE 23, 2016

Sqoop is compatible with all JDBC compatible databases. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Apache Sqoop uses Hadoop MapReduce to get data from relational databases and stores it on HDFS. Data import in sqoop is not event driven.

Hadoop 40

Hadoop MySQL Relational Database Java 40

ProjectPro

AUGUST 9, 2018

Amazon S3 (Simple Storage Service) Access Logs: Amazon S3 Access logs record information about individual requests made to the Amazon S3 buckets and can be used to analyze traffic patterns, troubleshoot, and perform security and access auditing. The log files may also be queried from a specific database table.

AWS 40

AWS Amazon Web Services Cloud Computing Database 40

Cloudera

JUNE 16, 2022

For governance and security teams, the questions revolve around chain of custody, audit, metadata, access control, and lineage. We had to build the streaming data pipeline that new data has to move through before it can be persisted and then provide business teams access to that pipeline for them to build data products.”

Kafka 84

Kafka Manufacturing Data Lake SQL 84

AltexSoft

MAY 12, 2023

It is commonly stored in relational database management systems (DBMSs) such as SQL Server, Oracle, and MySQL, and is managed by data analysts and database administrators. For example, developers can use Twitter API to access and collect public tweets, user profiles, and other data from the Twitter platform.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

MARCH 14, 2023

That’s why some MDS tools are commercial distributions designed to be low-code or even no-code, making them accessible to data practitioners with minimal technical expertise. Rather than having data limited to a select group of individuals, with modern data stack tools, everyone within an organization can query and access the data they need.

IT 59

IT Data Warehouse Data Governance Data Lake 59