Cloudera

SEPTEMBER 15, 2022

Mark: While most discussions of modern data platforms focus on comparing the key components, it is important to understand how they all fit together. The collection of source data shown on your left is composed of both structured and unstructured data from the organization’s internal and external sources.

Data Lake 83

Data Lake Data Architecture Data-driven Data Warehouse 83

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. This is especially helpful when handling massive amounts of big data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. This performance innovation allows Nasdaq to have a multi-use data lake between teams.

Data Warehouse 56

Data Warehouse Data Lake Unstructured Data Optimization 56

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.

Data Lake 111

Data Lake Metadata Optimization Statistics 111

Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. The ability to connect straight to the source allows knowledge workers to work natively in spreadsheets, pulling data directly from true data sources like the data warehouse or data lake.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

BizAcuity

APRIL 14, 2022

For example, one company let all its data scientists access and make changes to their data tables for report generation, which caused inconsistency and cost the company significantly. The best way to avoid poor data quality is having a strict data governance system in place. Unstructured Data Management.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

CIO Business Intelligence

MAY 24, 2022

The survey found the mean number of data sources per organisation to be 400, and more than 20 percent of companies surveyed to be drawing from 1,000 or more data sources to feed business intelligence and analytics systems. However, more than 99 percent of respondents said they would migrate data to the cloud over the next two years.

Data-driven 98

Data-driven Data Lake Data Warehouse Cost-Benefit 98

IBM Big Data Hub

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

Data Architecture 65

Data Architecture Data Lake Machine Learning Data Governance 65

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 64

Data Lake Data Governance Data Warehouse Modeling 64

Alation

APRIL 19, 2022

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration. What Is the Role of the Cloud in Data Modernization?

Cost-Benefit 52

Cost-Benefit Data Governance Manufacturing Data Architecture 52