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. This often involves such operations as data harmonization, mastering, and enrichment with metadata. Enrichment with metadata is another important thing.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

U-Next

AUGUST 23, 2022

Tableau may be used for: controlling metadata. Ready data connections are accessible when Tableau is opened, allowing you to access any dataset. Users have access to the produced dashboards as a dynamic file, and the people that get the dashboards utilize Tableau Reader to examine the file. Tableau: Why Use It?

BI 52

BI Amazon Web Services Business Intelligence Database 52

Cloudera

FEBRUARY 9, 2021

A typical approach that we have seen in customers’ environments is that ETL applications pull data with a frequency of minutes and land it into HDFS storage as an extra Hive table partition file. In this way, the analytic applications are able to turn the latest data into instant business insights. Design Detail.

Data Warehouse 70

Data Warehouse Cloud Kafka Cloud Storage 70

Cloudera

NOVEMBER 22, 2021

For example, organizations with existing on-premises environments that are trying to extend their analytical environment to the public cloud and deploy hybrid-cloud use cases need to build their own metadata synchronization and data replication capabilities. benchmarking study conducted by independent 3rd party ). Conclusion .

Government 92

Government Hadoop Data Security Data Warehouse 92

ProjectPro

JANUARY 31, 2023

Every map/reduce action carried out by the Hadoop framework on the data nodes has access to cached files. As a result, the data files in the task assigned can access the cache file as a local file. NameNode is often given a large space to contain metadata for large-scale files. Here, data is accessible even if the machine fails.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Knowledge Hut

JULY 26, 2023

Data Access Layer: The data access layer function is to create a connection between the application and the database. Reporting and Analytics: These components enable users to obtain valuable insights from data and generate reports or visualizations for decision-making or reporting. Database Software- Document Store (e.g.-MongoDB):

Database 52

Database NoSQL Telecommunication MongoDB 52

Cloudera

NOVEMBER 13, 2017

Cloud PaaS takes this a step further and allows users to focus directly on building data pipelines, training machine learning models, developing analytics applications — all the value creation efforts, vs the infrastructure operations.

Cloud 40

Cloud Big Data Metadata Machine Learning 40

Cloudera

DECEMBER 7, 2017

That data may be hard to discover for other users and other applications. Worse, the metadata and context associated with that data may be lost forever if a transient cluster is shut down and the resources released. A way to leverage the benefits of cloud for multi-disciplinary analytics, without all of those problems.

Building 40

Building Management Government BI 40

AltexSoft

JULY 18, 2023

It has in-memory computing capabilities to deliver speed, a generalized execution model to support various applications, and Java, Scala, Python, and R APIs. Spark Streaming enhances the core engine of Apache Spark by providing near-real-time processing capabilities, which are essential for developing streaming analytics applications.

Big Data 52

Big Data Data Process Process Hadoop 52

phData: Data Engineering

JULY 18, 2023

Imagine a world where all of your data is organized, easily accessible, and routinely leveraged to drive impactful outcomes. Demands on the cloud data warehouse are also evolving to require it to become more of an all-in-one platform for an organization’s analytics needs. Read more here.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

AltexSoft

OCTOBER 21, 2022

Another security measure is an audit log to track access. The tool takes care of storing metadata about partitions and brokers. Hadoop fits heavy, not time-critical analytics applications that generate insights for long-term planning and strategic decisions. Large user community. ZooKeeper issue. Kafka vs ETL.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93