Cloudera

OCTOBER 11, 2022

Al needs machine learning (ML), ML needs data science. Data science needs analytics. And they all need lots of data. The takeaway – businesses need control over all their data in order to achieve AI at scale and digital business transformation. Doing data at scale requires a data platform. .

Data Science 94

Data Science Snapshot Data Warehouse Metadata 94

AWS Big Data

JULY 20, 2023

Using Apache Iceberg’s compaction results in significant performance improvements, especially for large tables, making a noticeable difference in query performance between compacted and uncompacted data. These files are then reconciled with the remaining data during read time.

Data Lake 94

Data Lake Analytics Snapshot Data Quality 94

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 124

Analytics IoT Data-driven Snapshot 124

AWS Big Data

NOVEMBER 6, 2023

You can see the time each task spends idling while waiting for the Redshift cluster to be created, snapshotted, and paused. Airflow will cache variables and connections locally so that they can be accessed faster during DAG parsing, without having to fetch them from the secrets backend, environments variables, or metadata database.

Metrics 117

Metrics Metadata Snapshot Management 117

AWS Big Data

APRIL 3, 2024

If the asset has AWS Glue Data Quality enabled, you can now quickly visualize the data quality score directly in the catalog search pane. By selecting the corresponding asset, you can understand its content through the readme, glossary terms , and technical and business metadata.

Data Quality 104

Data Quality Visualization Metadata Metrics 104

Cloudera

NOVEMBER 15, 2024

However, there is a fundamental challenge standing in the way of being successful: data. Optimized for analytics: Iceberg tables are designed to deliver analytics faster and more effectively. The metadata-driven approach ensures quick query planning so defenders don’t have to deal with slow processes when they need fast answers.

Analytics 59

Analytics Metadata Snapshot Data-driven 59

Cloudera

MARCH 15, 2023

The record in the “outbox” table contains information about the event that happened inside the application, as well as some metadata that is required for further processing or routing. NOTE: Cloudera Data Platform (CDP) is a hybrid data platform designed for unmatched freedom to choose—any cloud, any analytics, any data.

Data-driven 91

Data-driven Snapshot Publishing Metadata 91

AWS Big Data

MARCH 25, 2024

Furthermore, data events are filtered, enriched, and transformed to a consumable format using a stream processor. The result is made available to the application by querying the latest snapshot. This allows the model to adapt to the latest changes in price and availability.

Data Lake 105

Data Lake Unstructured Data Management Snapshot 105

AWS Big Data

JUNE 12, 2023

Organizations across the world are increasingly relying on streaming data, and there is a growing need for real-time data analytics, considering the growing velocity and volume of data being collected. For more information about checkpointing, see the appendix at the end of this post.

Management 87

Management Metadata Internet of Things Testing 87

AWS Big Data

MARCH 3, 2023

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

Data Lake 91

Data Lake Dashboards Metrics Metadata 91

AWS Big Data

AUGUST 16, 2023

We fetch the metadata of the users_xxxxxx table from Athena. The following are a few important considerations regarding how the Lambda function handles Iceberg table metadata changes: In this approach, target metadata takes precedence during DML operations. It’s imperative that the source and target metadata match.

Data Lake 79

Data Lake Metadata Testing Snapshot 79

AWS Big Data

OCTOBER 23, 2024

Running HBase on Amazon S3 has several added benefits, including lower costs, data durability, and easier scalability. And during HBase migration, you can export the snapshot files to S3 and use them for recovery. HBase provided by other cloud platforms doesn’t support snapshots.

Snapshot 104

Snapshot Recreation/Entertainment Testing Data Processing 104

Cloudera

OCTOBER 10, 2024

The open data lakehouse is quickly becoming the standard architecture for unified multifunction analytics on large volumes of data. It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse.

Optimization 84

Optimization Snapshot Data Lake Cost-Benefit 84

Cloudera

NOVEMBER 15, 2024

However, there is a fundamental challenge standing in the way of being successful: data. Optimized for analytics: Iceberg tables are designed to deliver analytics faster and more effectively. The metadata-driven approach ensures quick query planning so defenders don’t have to deal with slow processes when they need fast answers.

Analytics 84

Analytics Metadata Snapshot Data-driven 84

AWS Big Data

FEBRUARY 18, 2025

To optimize their security operations, organizations are adopting modern approaches that combine real-time monitoring with scalable data analytics. They are using data lake architectures and Apache Iceberg to efficiently process large volumes of security data while minimizing operational overhead.

Snapshot 76

Snapshot Optimization Data Lake Metadata 76

Cloudera

DECEMBER 3, 2024

REST Catalog Value Proposition It provides open, metastore-agnostic APIs for Iceberg metadata operations, dramatically simplifying the Iceberg client and metastore/engine integration. It provides real time metadata access by directly integrating with the Iceberg-compatible metastore. spark.sql(SELECT * FROM airlines_data.carriers).show()

Metadata 84

Metadata Data Warehouse ROI Snapshot 84

AWS Big Data

NOVEMBER 6, 2024

For example, you can write some records using a batch ETL Spark job and other data from a Flink application at the same time and into the same table. Third, it allows scenarios such as time travel and rollback, so you can run SQL queries on a point-in-time snapshot of your data, or rollback data to a previously known good version.

Metadata 109

Metadata Data Lake Management Internet of Things 109

AWS Big Data

DECEMBER 19, 2024

OTFs, such as Iceberg, address key limitations in traditional data lakes by offering features like ACID transactions, which maintain data consistency across concurrent operations, and compaction, which helps manage the issue of small files by merging them efficiently. The data is sent to Amazon MSK, which acts as a streaming table.

Data Lake 92

Data Lake IoT Metadata Testing 92

DataKitchen

AUGUST 8, 2023

Data Observability leverages five critical technologies to create a data awareness AI engine: data profiling, active metadata analysis, machine learning, data monitoring, and data lineage. It’s primarily used to understand where data came from and its transformations.

Data Quality 130

Data Quality Testing Snapshot Reporting 130

DataKitchen

JANUARY 23, 2023

To capture a more complete picture of the data’s journey, it is important to have a DataOps Observability system in place. Data lineage is static and often lags by weeks or months. Data lineage is often considered static because it is typically based on snapshots of data and metadata taken at a specific time.

Testing 130

Testing Data Governance Data Quality Data-driven 130