Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. LPG lacks schema and semantics, which makes it inappropriate for publishing and sharing of data. This makes LPGs inflexible.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping is important for several reasons.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. Multi-channel publishing of data services. Does Data Virtualization support web data integration?

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

AWS Big Data

OCTOBER 11, 2023

Under the Transparency in Coverage (TCR) rule , hospitals and payors to publish their pricing data in a machine-readable format. Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics.

Visualization 98

Visualization Dashboards Data-driven Gap analysis 98

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 104

Data Lake Management Metrics Data Warehouse 104

Jet Global

MARCH 14, 2024

Jet streamlines many aspects of data administration, greatly improving data solutions built on Microsoft Fabric. It enhances analytics capabilities, streamlines migration, and enhances data integration. Through Jet’s integration with Fabric, your organization can better handle, process, and use your data.

Analytics 52

Analytics Management Reporting Enterprise 52

Jet Global

MAY 1, 2023

Requirement Multi-Source Data Blending Data from multiple sources is compiled and the output is a single view, metric, or visualization. Data Transformation and Enrichment Data can be enriched for analysis. Metadata Self-service analysis is made easy with user-friendly naming conventions for tables and columns.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52