AltexSoft

SEPTEMBER 23, 2021

The main purpose of a DW is to enable analytics: It is designed to source raw historical data, apply transformations, and store it in a structured format. This type of storage is a standard part of any business intelligence (BI) system, an analytical interface where users can query data to make business decisions.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

AltexSoft

OCTOBER 21, 2022

After trying all options existing on the market — from messaging systems to ETL tools — in-house data engineers decided to design a totally new solution for metrics monitoring and user activity tracking which would handle billions of messages a day. Kafka is designed to handle numerous clients from both sides. ZooKeeper issue.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

ProjectPro

JANUARY 31, 2023

HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. Scripting: Designing test cases necessitates a high level of scripting expertise. Diagnostic Solution: A custom solution is required to design and remove the bottleneck to improve performance. No reliability exists.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Cloudera

FEBRUARY 8, 2024

Apache Iceberg is a high-performance open table format for petabyte-scale analytic datasets. It has been designed and developed as an open community standard to ensure compatibility across languages and implementations. The snapshotId of the source tables involved in the materialized view are also maintained in the metadata.

Metadata 91

Metadata Data Warehouse BI AWS 91

Cloudera

SEPTEMBER 15, 2022

It was designed as a native object store to provide extreme scale, performance, and reliability to handle multiple analytics workloads using either S3 API or the traditional Hadoop API. A unified design represents files, directories, and objects stored in a single system. Bringing files and objects under one roof. Bucket types.

Systems 87

Systems Hadoop Metadata Telecommunication 87

Cloudera

NOVEMBER 8, 2022

It enables cloud-native applications to store and process mass amounts of data in a hybrid multi-cloud environment and on premises. These could be traditional analytics applications like Spark, Impala, or Hive, or custom applications that access a cloud object store natively. This results in write amplification.

Metadata 84

Metadata Algorithm Hadoop Cloud 84

Cloudera

MARCH 6, 2018

This leads to extra cost, effort, and risk to stitch together a sub-optimal platform for multi-disciplinary, cloud-based analytics applications. If catalog metadata and business definitions live with transient compute resources, they will be lost, requiring work to recreate later and making auditing impossible.

Cloud 40

Cloud Metadata Big Data AWS 40

U-Next

AUGUST 23, 2022

Tableau may be used for: controlling metadata. User-friendly Design: This is Tableau’s biggest asset, and it is designed from the ground up for those without any coding or technical background. You may communicate your ideas more clearly than you could with only words alone by using well-designed visuals and charts.

BI 52

BI Amazon Web Services Business Intelligence Database 52

phData: Data Engineering

JULY 18, 2023

Central Source of Truth for Analytics A Cloud Data Warehouse (CDW) is a type of database that provides analytical data processing and storage capabilities within a cloud-based infrastructure. Modern Data Stacks embrace governance as a core design principle. Modern data businesses need modern data governance.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52