AWS Big Data

APRIL 3, 2024

Iceberg tables maintain metadata to abstract large collections of files, providing data management features including time travel, rollback, data compaction, and full schema evolution, reducing management overhead. Snowflake integrates with AWS Glue Data Catalog to retrieve the snapshot location.

Data Lake 105

Data Lake Snapshot Metadata Data Architecture 105

Cloudera

FEBRUARY 8, 2024

The snapshotId of the source tables involved in the materialized view are also maintained in the metadata. Subsequently, these snapshot IDs are used to determine the delta changes that should be applied to the materialized view rows. Furthermore, it is partitioned on the d_year column.

Snapshot 91

Snapshot Metadata Cost-Benefit Data Warehouse 91

AWS Big Data

DECEMBER 4, 2024

The company is looking for an efficient, scalable, and cost-effective solution to collecting and ingesting data from ServiceNow, ensuring continuous near real-time replication, automated availability of new data attributes, robust monitoring capabilities to track data load statistics, and reliable data lake foundation supporting data versioning.

Data Integration 97

Data Integration Data Lake Statistics Data-driven 97

Cloudera

NOVEMBER 13, 2020

Impala’s planner does not do exhaustive cost-based optimization. Instead, it makes cost-based decisions with more limited scope (for example when comparing join strategies) and applies rule-based and heuristic optimizations for common query patterns. Metadata Caching. More on this below. Execution Engine.

Optimization 143

Optimization Metadata Statistics Cost-Benefit 143

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale. For updates, previous versions of the old values of a record may be retained until a similar process is run.

Data Lake 125

Data Lake Metadata Statistics Optimization 125

AWS Big Data

NOVEMBER 16, 2023

In the following sections, we discuss the most common areas of consideration that are critical for Data Vault implementations at scale: data protection, performance and elasticity, analytical functionality, cost and resource management, availability, and scalability.

Enterprise 96

Enterprise Data Warehouse Snapshot Cost-Benefit 96

AWS Big Data

OCTOBER 11, 2023

To reap the benefits of cloud computing, like increased agility and just-in-time provisioning of resources, organizations are migrating their legacy analytics applications to AWS. Frequent materialized view refreshes on top of constantly changing base tables due to streamed data can lead to snapshot isolation errors.

Management 117

Management Metadata Analytics Dashboards 117

Cloudera

JULY 13, 2022

The service provides simple, easy-to-use, and feature-rich data movement capability to deliver data and metadata where it is needed, and has secure data backup and disaster recovery functionality. In this method, you prepare the data for migration, and then set up the replication plugin to use a snapshot to migrate your data.

Snapshot 91

Snapshot Management Cost-Benefit Metadata 91

Cloudera

APRIL 3, 2023

Every table change creates an Iceberg snapshot, this helps to resolve concurrency issues and allows readers to scan a stable table state every time. The table metadata is stored next to the data files under a metadata directory, which allows multiple engines to use the same table simultaneously.

Data Warehouse 82

Data Warehouse Snapshot Metadata Cost-Benefit 82

AWS Big Data

AUGUST 6, 2024

This post elaborates on the drivers of the migration and its achieved benefits. At a high level, the core of Langley’s architecture is based on a set of Amazon Simple Queue Service (Amazon SQS) queues and AWS Lambda functions, and a dedicated RDS database to store ETL job data and metadata.

Cost-Benefit 103

Cost-Benefit Metadata Snapshot Metrics 103

AWS Big Data

AUGUST 23, 2023

With managed domains, you can use advanced capabilities at no extra cost such as cross-cluster search, cross-cluster replication, anomaly detection, semantic search, security analytics, and more. Built on OpenSearch Serverless, the vector engine inherits and benefits from its robust architecture. Additional field types OpenSearch 2.7

Snapshot 97

Snapshot Dashboards Visualization Metrics 97

Cloudera

MARCH 23, 2022

In fact, we recently announced the integration with our cloud ecosystem bringing the benefits of Iceberg to enterprises as they make their journey to the public cloud, and as they adopt more converged architectures like the Lakehouse. Iceberg, on the other hand, is an open table format that works with open file formats to avoid this coupling.

Metadata 92

Metadata Data Architecture Machine Learning Cost-Benefit 92

AWS Big Data

MARCH 10, 2023

Iceberg employs internal metadata management that keeps track of data and empowers a set of rich features at scale. Moreover, many customers are looking for an architecture where they can combine the benefits of a data lake and a data warehouse in the same storage location. The Iceberg table is synced with the AWS Glue Data Catalog.

Data Lake 116

Data Lake Sales Data Warehouse Snapshot 116

Cloudera

FEBRUARY 14, 2024

It offers several benefits such as schema evolution, hidden partitioning, time travel, and more that improve the productivity of data engineers and data analysts. Problem with too many snapshots Everytime a write operation occurs on an Iceberg table, a new snapshot is created. See Write properties.

Optimization 59

Optimization Strategy Snapshot Metadata 59

Cloudera

JULY 14, 2023

However, as there are already 25 million terabytes of data stored in the Hive table format, migrating existing tables in the Hive table format into the Iceberg table format is necessary for performance and cost. They also provide a “ snapshot” procedure that creates an Iceberg table with a different name with the same underlying data.

Snapshot 70

Snapshot Data Warehouse Metadata Testing 70

IBM Big Data Hub

JULY 6, 2022

With the average cost of bad data reaching $15M, 2 ignoring the problem is a significant pitfall. . starts at the data source, collecting data pipeline metadata across key solutions in the modern data stack like Airflow, dbt, Databricks and many more. Businesses of all sizes, in all industries are facing a data quality problem.

Metadata 56

Metadata Data Quality Snapshot Cost-Benefit 56

Domino Data Lab

JUNE 26, 2019

On the flip side, when data scientists mark a project as complete with a description of the project conclusion, Domino also captures this metadata for project tracking and future references. All of this metadata captured can be useful for organizational learning, organize projects and help to avoid similar issues in the future. .

Data Science 65

Data Science Dashboards Metadata Snapshot 65

Alation

JULY 28, 2022

However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing. There are tools to replicate and snapshot data, plus tools to scale and improve performance.” Data aggregation is another key benefit the cloud delivers.

Data Warehouse 69

Data Warehouse Cost-Benefit Data-driven Data Governance 69

AWS Big Data

JANUARY 17, 2024

By preserving historical versions, data lake time travel provides benefits such as auditing and compliance, data recovery and rollback, reproducible analysis, and data exploration at different points in time. The following are some highlighted steps: Run a snapshot query. %%sql You can now follow the steps in the notebook.

Data Lake 107

Data Lake Snapshot Big Data Data-driven 107

AWS Big Data

MARCH 25, 2024

The result is made available to the application by querying the latest snapshot. The snapshot constantly updates through stream processing; therefore, the up-to-date data is provided in the context of a user prompt to the model. This allows the model to adapt to the latest changes in price and availability.

Data Lake 104

Data Lake Unstructured Data Management Snapshot 104

Wayne Yaddow

MARCH 14, 2025

Snapshot testing augments debugging capabilities by recording past table states, facilitating the identification of unforeseen spikes, declines, or abnormalities before their effect on production systems. Workaround: Implement custom metadata tracking scripts or use dbt Clouds freshness monitoring.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

CIO Business Intelligence

MARCH 5, 2025

In AI governance: Act now, thrive later , author Stephen Kaufman provides prevailing guidance that, Companies need to create and implement AI governance policies so that AI can deliver benefits to the organization and the customer, to provide a fair, safe and inclusive system that is trusted by the users.

Risk 121

Risk Risk Management Measurement Modeling 121

AWS Big Data

DECEMBER 20, 2024

Some of the challenges that motivated the modernization were the high cost of maintenance, lack of agility to scale computing at specific times, job queuing, lack of innovation when it came to acquiring more modern technologies, complex automation of the infrastructure and applications, and the inability to develop locally.

Metadata 111

Metadata Data-driven Snapshot Data Lake 111

Cloudera

OCTOBER 10, 2024

Iceberg has many features that drastically reduce the work required to deliver a high-performance view of the data, but many of these features create overhead and require manual job execution to optimize for performance and costs. Actual results will vary depending on actual usage.

Optimization 84

Optimization Snapshot Data Lake Cost-Benefit 84

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 103

Snapshot Recreation/Entertainment Testing Data Processing 103

AWS Big Data

DECEMBER 19, 2024

Data lakes were originally designed to store large volumes of raw, unstructured, or semi-structured data at a low cost, primarily serving big data and analytics use cases. By using features like Icebergs compaction, OTFs streamline maintenance, making it straightforward to manage object and metadata versioning at scale.

Data Lake 91

Data Lake IoT Metadata Testing 91

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. Data Lineage, a form of static analysis , is like a snapshot or a historical record describing data assets at a specific time.

Data Quality 130

Data Quality Testing Snapshot Reporting 130