Remove Dashboards Remove Metadata Remove Optimization Remove Unstructured Data
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Cloudera Named a Visionary in the Gartner MQ for Cloud DBMS

Cloudera

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies.

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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. Cold storage is optimized to store infrequently accessed or historical data.

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The new challenges of scale: What it takes to go from PB to EB data scale

CIO Business Intelligence

To accomplish this, we will need additional data center space, more storage disks and nodes, the ability for the software to scale to 1000+PB of data, and increased support through additional compute nodes and networking bandwidth. We know the global volume of data will only grow larger and more difficult to navigate.

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Top 10 Key Features of BI Tools in 2020

FineReport

They prefer self-service development, interactive dashboards, and self-service data exploration. To put it bluntly, users increasingly want to do their own data analysis without having to find support from the IT department. Metadata management. Analytics dashboards. Mobile dashboard made with FineReport.

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How Ruparupa gained updated insights with an Amazon S3 data lake, AWS Glue, Apache Hudi, and Amazon QuickSight

AWS Big Data

The data lake implemented by Ruparupa uses Amazon S3 as the storage platform, AWS Database Migration Service (AWS DMS) as the ingestion tool, AWS Glue as the ETL (extract, transform, and load) tool, and QuickSight for analytic dashboards. Data had to be manually processed by data analysts, and data mining took a long time.

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Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback.

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How to get powerful and actionable insights from any and all of your data, without delay

Cloudera

They were not able to quickly and easily query and analyze huge amounts of data as required. They also needed to combine text or other unstructured data with structured data and visualize the results in the same dashboards. You can link dashboards and have them depend on each other.