Data Virtualization

OCTOBER 18, 2022

The post The Data Warehouse is Dead, Long Live the Data Warehouse, Part I appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information. In times of potentially troublesome change, the apparent paradox and inner poetry of these.

Data Warehouse 98

Data Warehouse ROI Data Integration Internet of Things 98

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. Table metadata is fetched from AWS Glue. The generated Athena SQL query is run.

Metadata 103

Metadata Data Lake Modeling Data Warehouse 103

erwin

FEBRUARY 7, 2019

Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. As such, traditional – and mostly manual – processes associated with data management and data governance have broken down.

Metadata 96

Metadata Insurance Data-driven Cost-Benefit 96

Cloudera

DECEMBER 11, 2020

In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to EMR 6.0 (also powered by Apache Hive-LLAP) on Amazon using the TPC-DS 2.9 Cloudera Data Warehouse vs EMR. Learn more about Cloudera Data Warehouse on CDP.

Data Warehouse 111

Data Warehouse Metadata Machine Learning Measurement 111

Cloudera

JANUARY 15, 2021

Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. The results demonstrate superior price performance of Cloudera Data Warehouse on the full set of 99 queries from the TPC-DS benchmark. Introduction.

Data Warehouse 102

Data Warehouse Cost-Benefit Consulting Interactive 102

Octopai

DECEMBER 12, 2021

What enables you to use all those gigabytes and terabytes of data you’ve collected? Metadata is the pertinent, practical details about data assets: what they are, what to use them for, what to use them with. Without metadata, data is just a heap of numbers and letters collecting dust. Where does metadata come from?

Metadata 98

Metadata Management Data Quality Data Governance 98

Cloudera

MAY 17, 2021

Making a decision on a cloud data warehouse is a big deal. Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform.

Data Warehouse 92

Data Warehouse Measurement Reporting Testing 92

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

AWS Big Data

MARCH 27, 2023

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure. Tags allows you to assign metadata to your AWS resources. You can define your own key and value for your resource tag, so that you can easily manage and filter your resources.

Data Warehouse 98

Data Warehouse Management Snapshot Data Lake 98

datapine

MAY 29, 2019

One of the BI architecture components is data warehousing. Organizing, storing, cleaning, and extraction of the data must be carried by a central repository system, namely data warehouse, that is considered as the fundamental component of business intelligence. What Is Data Warehousing And Business Intelligence?

Business Intelligence 196

Business Intelligence Data Warehouse Dashboards Visualization 196

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. Try Cloudera Data Warehouse (CDW) by signing up for a 60 day trial , or test drive CDP.

Data Warehouse 87

Data Warehouse Snapshot Metadata Cost-Benefit 87

Cloudera

SEPTEMBER 24, 2020

Some of the most powerful results come from combining complementary superpowers, and the “dynamic duo” of Apache Hive LLAP and Apache Impala, both included in Cloudera Data Warehouse , is further evidence of this. Both Impala and Hive can operate at an unprecedented and massive scale, with many petabytes of data.

Data Warehouse 75

Data Warehouse Metadata Interactive Dashboards 75

Alation

JULY 28, 2022

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

Data Warehouse 69

Data Warehouse Cost-Benefit Data-driven Data Governance 69

DataKitchen

AUGUST 3, 2021

The past decades of enterprise data platform architectures can be summarized in 69 words. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Note, this is based on a post by Zhamak Dehghani of Thoughtworks. .

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

Octopai

FEBRUARY 12, 2020

Like any good puzzle, metadata management comes with a lot of complex variables. That’s why you need to use data dictionary tools, which can help organize your metadata into an archive that can be navigated with ease and from which you can derive good information to power informed decision-making. Why Have a Data Dictionary? #1

Metadata 72

Metadata Enterprise Management Data Warehouse 72

AWS Big Data

APRIL 6, 2023

We realized we needed a data warehouse to cater to all of these consumer requirements, so we evaluated Amazon Redshift. At the same time, we had to find a way to implement entitlements in our Amazon Redshift data warehouse with the same set of tags that we had already defined in Lake Formation.

Data Warehouse 98

Data Warehouse Data Lake Management Data-driven 98

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 73

Data Warehouse Cost-Benefit Metadata Management 73

erwin

JUNE 26, 2020

Given the value this sort of data-driven insight can provide, the reason organizations need a data catalog should become clearer. It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., Three Types of Metadata in a Data Catalog. Technical Metadata.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

CIO Business Intelligence

APRIL 25, 2024

Currently, a handful of startups offer “reverse” extract, transform, and load (ETL), in which they copy data from a customer’s data warehouse or data platform back into systems of engagement where business users do their work. It works in Salesforce just like any other native Salesforce data,” Carlson said.

Data Integration 119

Data Integration Data Lake Data Warehouse Metadata 119

Data Virtualization

DECEMBER 8, 2022

Reading Time: 3 minutes While cleaning up our archive recently, I found an old article published in 1976 about data dictionary/directory systems (DD/DS). Nowadays, we no longer use the term DD/DS, but “data catalog” or simply “metadata system”. It was written by L.

Metadata 69

Metadata IT Data Integration Publishing 69

AWS Big Data

NOVEMBER 26, 2024

This post was co-written with Dipankar Mazumdar, Staff Data Engineering Advocate with AWS Partner OneHouse. Data architecture has evolved significantly to handle growing data volumes and diverse workloads. The synchronization process in XTable works by translating table metadata using the existing APIs of these table formats.

Metadata 105

Metadata Data Lake Snapshot Cost-Benefit 105

AWS Big Data

NOVEMBER 14, 2024

You can learn how to query Delta Lake native tables through UniForm from different data warehouses or engines such as Amazon Redshift as an example of expanding data access to more engines. Both Delta Lake and Iceberg metadata files reference the same data files.

Metadata 121

Metadata Data Warehouse Big Data Data Lake 121

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. This results in less joins between the metric data in fact tables, and the dimensions. So let’s dive in! OLTP vs OLAP.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

AWS Big Data

NOVEMBER 7, 2024

Amazon Redshift is a fully managed, AI-powered cloud data warehouse that delivers the best price-performance for your analytics workloads at any scale. It enables you to get insights faster without extensive knowledge of your organization’s complex database schema and metadata. Your data is not shared across accounts.

Metadata 105

Metadata Sales Data Warehouse Optimization 105

Cloudera

DECEMBER 10, 2020

Why worry about costs with cloud-native data warehousing? Have you been burned by the unexpected costs of a cloud data warehouse? If not, before adopting a cloud data warehouse, consider the true costs of a cloud-native data warehouse. These costs impede the adoption of cloud-native data warehouses.

Data Warehouse 98

Data Warehouse Metadata Cost-Benefit Optimization 98

Data Virtualization

APRIL 21, 2022

Reading Time: 3 minutes First we had data warehouses, then came data lakes, and now the new kid on the block is the data lakehouse. But what is a data lakehouse and why should we develop one? In a way, the name describes what.

Data Lake 59

Data Lake Data Warehouse Data Integration Management 59

AWS Big Data

FEBRUARY 29, 2024

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. Data enrichment In addition, additional metadata may need to be extracted from the objects.

Data Governance 123

Data Governance Unstructured Data Metadata Data Lake 123

AWS Big Data

JULY 29, 2024

Amazon DataZone is a powerful data management service that empowers data engineers, data scientists, product managers, analysts, and business users to seamlessly catalog, discover, analyze, and govern data across organizational boundaries, AWS accounts, data lakes, and data warehouses.

Sales 108

Sales Data Warehouse Metadata Publishing 108

AWS Big Data

OCTOBER 25, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. The new technique captures real-time statistical metadata gathered during data ingestion without incurring additional computational overhead.

Statistics 105

Statistics Data Warehouse Metadata Data Lake 105

AWS Big Data

DECEMBER 17, 2024

Amazon Redshift , launched in 2013, has undergone significant evolution since its inception, allowing customers to expand the horizons of data warehousing and SQL analytics. Industry-leading price-performance Amazon Redshift offers up to three times better price-performance than alternative cloud data warehouses.

Data Lake 78

Data Lake Data Warehouse Data-driven Optimization 78

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 128

Data Warehouse Data Lake Analytics Machine Learning 128

CIO Business Intelligence

MAY 24, 2022

The rules are part of what the company calls the Data Quality Accelerator for Financial Services and can be used to accelerate the deployment of a data project and enable data-driven decision making. .

Finance 140

Finance Management Metadata Machine Learning 140

AWS Big Data

JUNE 10, 2024

When evolving such a partition definition, the data in the table prior to the change is unaffected, as is its metadata. Only data that is written to the table after the evolution is partitioned with the new definition, and the metadata for this new set of data is kept separately. SparkActions.get().expireSnapshots(iceTable).expireOlderThan(TimeUnit.DAYS.toMillis(7)).execute()

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

Timo Elliott

JANUARY 6, 2022

The data you’ve collected and saved over the years isn’t free. If storage costs are escalating in a particular area, you may have found a good source of dark data. Analyze your metadata. If you’ve yet to implement data governance, this is another great reason to get moving quickly. Data sense-making.

IT 135

IT Metadata Data-driven Data Governance 135

AWS Big Data

JULY 24, 2024

ActionIQ is a leading composable customer data (CDP) platform designed for enterprise brands to grow faster and deliver meaningful experiences for their customers. This post will demonstrate how ActionIQ built a connector for Amazon Redshift to tap directly into your data warehouse and deliver a secure, zero-copy CDP.

Data Warehouse 125

Data Warehouse Cost-Benefit Marketing Testing 125

Jen Stirrup

MARCH 29, 2023

Organisations are looking at ways of simplifying data; for example, through simple rebranding efforts to disguise the complexity. However, SAP Datasphere goes much deeper deeper than a simple rebranding; it is the next generation of SAP Data Warehouse Cloud.

Data Warehouse 121

Data Warehouse Metadata Data Integration Business Intelligence 121

AWS Big Data

APRIL 3, 2024

Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time. Apache Iceberg offers integrations with popular data processing frameworks such as Apache Spark, Apache Flink, Apache Hive, Presto, and more.

Data Lake 122

Data Lake Snapshot Metadata Data Architecture 122