erwin

DECEMBER 12, 2019

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. by up to 70 percent.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Cloudera

FEBRUARY 7, 2019

Enabling this transformation is the HDP platform, along with SAS Viya on Google Cloud , which has delivered machine learning models and personalization at scale. This has resulted in empowering team members to use innovative techniques to solve problems with advanced model management, to scale up quickly to meet performance needs.

Big Data 68

Big Data Data Analytics Analytics Data Architecture 68

Alation

APRIL 25, 2023

It’d be difficult to exaggerate the importance of data in today’s global marketplace, especially for firms which are going through digital transformation (DT). Using bad data, or the incorrect data can generate devastating results. This leads to data bottlenecks, breadlines… and lost opportunities.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

Alation

APRIL 25, 2023

It’d be difficult to exaggerate the importance of data in today’s global marketplace, especially for firms which are going through digital transformation (DT). Using bad data, or the incorrect data can generate devastating results. This leads to data bottlenecks, breadlines… and lost opportunities.

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

CIO Business Intelligence

NOVEMBER 25, 2022

Carhartt’s signature workwear is near ubiquitous, and its continuing presence on factory floors and at skate parks alike is fueled in part thanks to an ongoing digital transformation that is advancing the 133-year-old Midwest company’s operations to make the most of advanced digital technologies, including the cloud, data analytics, and AI.

Data Lake 127

Data Lake Data Warehouse Unstructured Data Data Architecture 127

AWS Big Data

NOVEMBER 15, 2023

The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse. In ELT, raw data is loaded into the data warehouse first, then it’s transformed directly within the warehouse.

Dashboards 96

Dashboards Analytics Metadata Data Warehouse 96

Jen Stirrup

MARCH 29, 2023

However, to turn data into a business problem, organizations need support to move away from technical issues to start getting value as quickly as possible. SAP Datasphere simplifies data integration, cataloging, semantic modeling, warehousing, federation, and virtualization through a unified interface. Why is this interesting?

Metadata 121

Metadata Data Warehouse Data Integration Business Intelligence 121

Ontotext

FEBRUARY 26, 2024

However, it still requires more effort than building a single-purpose graph, like a labeled property graph (LPG), where you can whiteboard your graph model in an hour. Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. RDF vs LPG?

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

CIO Business Intelligence

NOVEMBER 7, 2023

For years, IT and business leaders have been talking about breaking down the data silos that exist within their organizations. Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever.

Data Warehouse 140

Data Warehouse Digital Transformation Data-driven Reporting 140

IBM Big Data Hub

AUGUST 4, 2023

Data democratization, much like the term digital transformation five years ago, has become a popular buzzword throughout organizations, from IT departments to the C-suite. It’s often described as a way to simply increase data access, but the transition is about far more than that.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

Birst BI

FEBRUARY 25, 2020

Managing large-scale data warehouse systems has been known to be very administrative, costly, and lead to analytic silos. The good news is that Snowflake, the cloud data platform, lowers costs and administrative overhead. agentless) Birst to Snowflake real-time connector. What gaps does the joint solution address in the market?

Data Warehouse 52

Data Warehouse Cost-Benefit Data Architecture Enterprise 52

CIO Business Intelligence

APRIL 25, 2022

Similarly, many organizations have built data architectures to remain competitive, but have instead ended up with a complex web of disparate systems which may be slowing them down. Aligning data. A real-time data architecture should be designed with a set of aligned data streams that flow easily throughout the data ecosystem.

Data Architecture 96

Data Architecture Digital Transformation Data-driven Strategy 96

CIO Business Intelligence

AUGUST 3, 2023

But reaching all these goals, as well as using enterprise data for generative AI to streamline the business and develop new services, requires a proper foundation. That hard, ongoing work includes integrating siloed data, modeling, and understanding it, as well as maintaining and securing it over time.

Analytics 93

Analytics Data Lake Metadata Cost-Benefit 93

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 90

Data Lake Data Warehouse Data-driven B2B 90