Grouparoo

OCTOBER 6, 2021

This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams. For example, grouping the ones about metadata, discoverability, and column naming might have made a lot of sense.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

LinkedIn Engineering

JANUARY 16, 2024

At the heart of this system was a reliance on a relational database, Oracle, which served as the repository for all member restrictions data. These records held vital metadata linked to the restriction, including essential timestamps. This breach prompted resizing this data structure, effectively doubling its capacity.

Kafka 84

Kafka Relational Database Java Architecture 84

AltexSoft

JUNE 7, 2021

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.) For every data unit, the NameNode has to store metadata with names, access rights, locations, and so on. HDFS master-slave structure. Complex programming environment.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

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., Data and metadata. Basic metadata can be structural, descriptive, and administrative.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

AltexSoft

SEPTEMBER 23, 2021

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. In a nutshell, a model is a specific data structure a database can ingest. Enrichment with metadata is another important thing.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

AltexSoft

AUGUST 29, 2023

Such an object storage model allows metadata tagging and incorporating unique identifiers, streamlining data retrieval and enhancing performance. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. This will simplify further reading.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Cloudera

AUGUST 31, 2021

It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Here is the flow of events during migration by leveraging tools from Smart Data Transition Toolkit. Consideration of both data & metadata in the migration.

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

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. In NMDB we think of the media metadata universe in units of “DataStores”. A specific media analysis that has been performed on various media assets (e.g.,

Media 94

Media Database Metadata Data Schemas 94

ProjectPro

NOVEMBER 15, 2021

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. Presto allows you to query data stored in Hive, Cassandra, relational databases, and even bespoke data storage.

Big Data 52

Big Data Project Metadata Programming Language 52

AltexSoft

OCTOBER 3, 2022

A knowledge graph is a way to integrate data coming from a variety of disjointed sources in the network that connects different data entities — objects, people, events, situations, or abstract concepts — and depicts their semantic relationships. What is a knowledge graph? A knowledge graph example. General scenarios of using knowledge graphs.

Relational Database 52

Relational Database Banking Media Computer Science 52

Rockset

AUGUST 2, 2023

This transition can support new use cases that require a faster way to analyze events that was not needed until now. This enrichment data has changing schemas and new data providers are constantly being added to enhance the insights, making it challenging for Windward to support using relational databases with strict schemas.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

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

AltexSoft

DECEMBER 23, 2022

This process can involve extracting all rows and columns of data from a relational database, all records from a file, or all data from an API endpoint. To make this happen, a source system must be equipped with an automation mechanism or have an event-driven structure with webhooks. There are three key types of extraction.

Process 52

Process Building Raw Data Data Lake 52

AltexSoft

JUNE 26, 2023

Even now, in the era of ChatGPT , we still fill out paper-based documents and type numbers and words into an Excel file to capture events and record observations. Relational vs non-relational databases As we mentioned above, relational or SQL databases are designed for structured or tabular data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

SEPTEMBER 21, 2023

Analysis of logs, metrics, and security events. With Elasticsearch, you can aggregate and analyze large streams of logs, metrics, and security events in near real-time, making it indispensable for system monitoring and security information and event management (SIEM). Real-time behavior modeling with ML.

Engineering 52

Engineering NoSQL Programming Language Java 52

AltexSoft

MARCH 14, 2023

These sources commonly include databases, SaaS products, and event streams. Databases store key information that powers a company’s product, such as user data and product data. The ones that keep only relational data in a tabular format are called SQL or relational database management systems (RDBMSs).

IT 59

IT Data Warehouse Data Governance Data Lake 59

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

Confluent

MAY 29, 2019

In part 1 , we discussed an event streaming architecture that we implemented for a customer using Apache Kafka ® , KSQL from Confluent, and Kafka Streams. Building event streaming applications using KSQL is done with a series of SQL statements, as seen in this example. Introduction. KSQL primer.

Kafka 93

Kafka Management Bytes SQL 93

AltexSoft

OCTOBER 8, 2021

The platform provides features for event-based , data-based, and service-based integration styles. Oracle Data Integrator has the functionality that automatically analyzes metadata from various data stores, detects patterns, generates, and then applies data quality rules to identify any issues among actual values. Pre-built connectors.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

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. IE retrieves predefined information, such as names, event dates, or phone numbers, and organizes it into a database. Invest in data governance.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

NOVEMBER 22, 2021

StructType is a collection of StructField objects that determines column name, column data type, field nullability, and metadata. To define the columns, PySpark offers the pyspark.sql.types import StructField class, which has the column name (String), column type (DataType), nullable column (Boolean), and metadata (MetaData).

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 communication between the domains can be approached through data sharing APIs or event-streaming backbone with technologies like Kafka, for example. And whenever we started thinking, “Hey, that’s it.

Architecture 52

Architecture Data Lake Medical Datasets 52

Knowledge Hut

DECEMBER 19, 2023

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. Among other things, it can track changes made to a file or a whole set of files so that different versions can be referred to whenever required.

Java 98

Java Programming Language Architecture Database 98

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. Metadata contains information such as the source of data, how to access the data, users who may require the data and information about the data mart schema.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 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 Redshift Logs: Amazon Redshift logs collect and record information concerning database connections, any changes to user definitions, and activity. The logs can be used for security monitoring and troubleshooting any database-related issues. The log files may also be queried from a specific database table.

AWS 40

AWS Amazon Web Services Cloud Computing Database 40