AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 102

Data Lake Management Metrics Data Warehouse 102

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

Data Architecture 66

Data Architecture Metadata Data Lake Snapshot 66

AWS Big Data

MARCH 3, 2023

Although Tricentis has amassed such data over a decade, the data remains untapped for valuable insights. Each of these tools has its own reporting capabilities that make it difficult to combine the data for integrated and actionable business insights.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 69

Modeling Sales Data Warehouse Snapshot 69

AWS Big Data

JULY 28, 2023

Amazon Redshift is a petabyte-scale, enterprise-grade cloud data warehouse service delivering the best price-performance. Today, tens of thousands of customers run business-critical workloads on Amazon Redshift to cost-effectively and quickly analyze their data using standard SQL and existing business intelligence (BI) tools.

Data Lake 67

Data Lake Data Governance Data Warehouse Modeling 67

Domino Data Lab

JANUARY 11, 2021

Part of this challenge is that many organizations seek to align their data science workflows to data warehousing patterns and practices. This means trading off granularity and latency of data for structures that make it easier to write queries that aggregate, filter and group results for reporting purposes.

Recreation/Entertainment 103

Recreation/Entertainment Data Science Data Warehouse Modeling 103

Cloudera

APRIL 3, 2023

In this blog, we will share with you in detail how Cloudera integrates core compute engines including Apache Hive and Apache Impala in Cloudera Data Warehouse with Iceberg. We will publish follow up blogs for other data services. It allows us to independently upgrade the Virtual Warehouses and Database Catalogs.

Data Warehouse 82

Data Warehouse Snapshot Metadata Cost-Benefit 82

Corinium

APRIL 25, 2019

Then when there is a breach, it comes as a shock, “wow, I didn’t even know that application had access to so much sensitive data”. Step One in any data security program should first be to discover and classify datasets that are sensitive, and know where that data is, and understand who really needs it to do their jobs.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Cloudera

DECEMBER 15, 2022

Improve performance and overall manageability of Iceberg tables using the new table maintenance capabilities such as expiring old snapshots and removing their metadata, and compaction to combine small files for more efficient data processing. Read why the future of data lakehouses is open. ORC open file format support.

Metadata 80

Metadata Data Warehouse Snapshot Data Quality 80