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. See below. .

Data Lake 79

Data Lake Data Architecture Data-driven Data Warehouse 79

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. The many data warehouse systems designed in the last 30 years present significant difficulties in that respect.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. This blog focuses on governing spreadsheets that contain data, information, and metadata, and must themselves be governed.

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

IBM Big Data Hub

MAY 9, 2023

IBM today announced it is launching IBM watsonx.data , a data store built on an open lakehouse architecture, to help enterprises easily unify and govern their structured and unstructured data, wherever it resides, for high-performance AI and analytics. What is watsonx.data?

Data Warehouse 78

Data Warehouse Cost-Benefit Recreation/Entertainment Unstructured Data 78

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

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. QuerySurge – Continuously detect data issues in your delivery pipelines. Process Analytics.

Testing 307

Testing Machine Learning Consulting Data Quality 307

datapine

FEBRUARY 22, 2022

This should also include creating a plan for data storage services. Are the data sources going to remain disparate? Or does building a data warehouse make sense for your organization? For this purpose, you can think about a data governance strategy. Define a budget.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

CDW Research Hub

SEPTEMBER 15, 2020

Business leaders need to be able to quickly access data—and to trust the accuracy of that data—to make better decisions. Traditional data warehouses are often too slow and can’t handle large volumes of data or different types of semi-structured or unstructured data.

Business Intelligence 52

Business Intelligence Prescriptive Analytics Unstructured Data Data Warehouse 52

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 64

Data Architecture Data Lake Machine Learning Data Governance 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