Smart Data Collective

AUGUST 28, 2021

Data lakes and data warehouses are probably the two most widely used structures for storing data. In this article, we will explore both, unfold their key differences and discuss their usage in the context of an organization. Data Warehouses and Data Lakes in a Nutshell. Target User Group.

Data Lake 139

Data Lake Data Warehouse Unstructured Data Structured Data 139

Ontotext

JANUARY 6, 2021

According to this article , it costs $54,500 for every kilogram you want into space. That means removing errors, filling in missing information and harmonizing the various data sources so that there is consistency. Once that is done, data can be transformed and enriched with metadata to facilitate analysis.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

Cloudera

JUNE 25, 2021

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. Visit this community article for step-by-step details.

Data Lake 68

Data Lake Metadata Unstructured Data Management 68

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.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Ontotext

DECEMBER 15, 2022

But whatever their business goals, in order to turn their invisible data into a valuable asset, they need to understand what they have and to be able to efficiently find what they need. Enter metadata. It enables us to make sense of our data because it tells us what it is and how best to use it.

Metadata 52

Metadata Unstructured Data Structured Data Enterprise 52

Ontotext

FEBRUARY 26, 2024

RED’s focus on news content serves a pivotal function: identifying, extracting, and structuring data on events, parties involved, and subsequent impacts. Quality assurance process, covering gold standard creation , extraction quality monitoring, measurement, and reporting via Ontotext Metadata Studio.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

FineReport

FEBRUARY 5, 2020

Metadata management. Users can centrally manage metadata, including searching, extracting, processing, storing, sharing metadata, and publishing metadata externally. The metadata here is focused on the dimensions, indicators, hierarchies, measures and other data required for business analysis. of BI pages.

Metadata 98

Metadata Dashboards Informatics Visualization 98