AWS Big Data

AUGUST 1, 2024

Migrating to Amazon Redshift offers organizations the potential for improved price-performance, enhanced data processing, faster query response times, and better integration with technologies such as machine learning (ML) and artificial intelligence (AI).

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

AWS Big Data

FEBRUARY 1, 2023

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Cloudera

DECEMBER 15, 2022

With in-place table migration, you can rapidly convert to Iceberg tables since there is no need to regenerate data files. Newly generated metadata will then point to source data files as illustrated in the diagram below. . Data quality using table rollback. Only metadata will be regenerated. ORC open file format support.

Metadata 80

Metadata Data Warehouse Snapshot Machine Learning 80

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

DECEMBER 9, 2024

Equally crucial is the ability to segregate and audit problematic data, not just for maintaining data integrity, but also for regulatory compliance, error analysis, and potential data recovery. One of its key features is the ability to manage data using branches.

Data Quality 126

Data Quality Publishing Snapshot Data Lake 126

AWS Big Data

JUNE 12, 2023

Therefore, it’s crucial to keep the schema definition in the Schema Registry and the Data Catalog table in sync. To avoid this, it’s recommended to use a data quality check mechanism to identify such anomalies and take appropriate action in case of unexpected behavior. Step 6} $ SCHEMA_NAME={VAL_OF_SchemaName– Ref.

Management 98

Management Metadata Internet of Things Testing 98

CIO Business Intelligence

APRIL 17, 2025

Moreover, 68% of vice presidents in charge of AI or data management already see their companies making decisions based on bad data all or most of the time, versus 47% of C-level IT leaders. To fix this data quality confidence gap, companies should focus on being more transparent across their org charts, Palaniappan advises.

Data-driven 130

Data-driven Data Quality Snapshot Dashboards 130

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. Enabling automatic compaction on Iceberg tables reduces metadata overhead on your Iceberg tables and improves query performance.

Data Lake 98

Data Lake IoT Metadata Testing 98