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

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

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

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

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

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

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

Cloudera

JUNE 16, 2022

In 2015, Cloudera became one of the first vendors to provide enterprise support for Apache Kafka, which marked the genesis of the Cloudera Stream Processing (CSP) offering. Today, CSP is powered by Apache Flink and Kafka and provides a complete, enterprise-grade stream management and stateful processing solution. Who is affected?

Kafka 84

Kafka Manufacturing Data Lake SQL 84

AltexSoft

MARCH 14, 2023

Many components of a modern data stack (such as Apache Airflow, Kafka, Spark, and others) are open-source and free. 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. Event streams.

IT 59

IT Data Warehouse Data Governance Data Lake 59