erwin

JULY 17, 2019

Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there. Constructing A Digital Transformation Strategy: Data Enablement. Many organizations prioritize data collection as part of their digital transformation strategy.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

CIO Business Intelligence

JANUARY 30, 2024

CSDDD is expected to make the reporting of ESG-related information a full-time job and fundamentally change how companies are structured around this reporting,” says Mentesana. What companies need more than anything is good data for ESG reporting. The complexity is at a much higher level.”

Reporting 105

Reporting Data Quality Strategy Data-driven 105

IBM Big Data Hub

DECEMBER 7, 2023

Initially, they were designed for handling large volumes of multidimensional data, enabling businesses to perform complex analytical tasks, such as drill-down , roll-up and slice-and-dice. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

OLAP 59

OLAP Slice and Dice Cost-Benefit Data Warehouse 59

Sisense

DECEMBER 11, 2019

The importance of giving this information to VCs reinforces how significant a role data plays in measuring and predicting growth and enabling companies and investors to gain insights that drive growth. Scott Castle, Sisense General Manager, Data Business. They’re no longer simply a repository for information.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

Sisense

JANUARY 13, 2020

From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire. And cloud data warehouses or data lakes give companies the capability to store these vast quantities of data. Data improves and streamlines production quality control.

Manufacturing 52

Manufacturing Data Lake Big Data Data Warehouse 52

Ontotext

AUGUST 4, 2023

Thanks to the metadata that the data fabric relies on, companies can also recognize different types of data, what is relevant, and what needs privacy controls; thereby, improving the intelligence of the whole information ecosystem. Data fabric does not replace data warehouses, data lakes, or data lakehouses.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

Alation

FEBRUARY 20, 2020

“The key point is that no organization governs information simply because it can. there has to be a business context, and the increasing realization of this context explains the rise of information stewardship applications.” – May 2018 Gartner Market Guide for Information Stewardship Applications. [2] -->.

Data Governance 52

Data Governance Data Lake Dashboards Big Data 52

Sisense

OCTOBER 6, 2020

Let’s consider the differences between the two, and why they’re both important to the success of data-driven organizations. Digging into quantitative data. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?” Qualitative data benefits: Unlocking understanding.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Alation

JANUARY 26, 2023

Many users struggle to access the information they need or understand its full context once that access is unlocked. What’s worse, just 3% of the data in a business enterprise meets quality standards. There’s also no denying that data management is becoming more important, especially to the public.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

AWS Big Data

JUNE 19, 2023

Security Lake automatically centralizes security data from cloud, on-premises, and custom sources into a purpose-built data lake stored in your account. With Security Lake, you can get a more complete understanding of your security data across your entire organization.

Publishing 88

Publishing Dashboards Visualization Management 88

Alation

FEBRUARY 20, 2020

Enterprises are… turning to data catalogs to democratize access to data, enable tribal data knowledge to curate information, apply data policies, and activate all data for business value quickly.”. In a recent webinar,“ Ready for a Machine Learning Data Catalog?

Machine Learning 52

Machine Learning Metadata Reporting Data-driven 52

Andrew White

JANUARY 11, 2021

In general, I would offer that information-based industries tend to be more advanced than non-information-based industries. As such banking, finance, insurance and media are good examples of information-based industries compared to manufacturing, retail, and so on. Data lakes don’t offer this nor should they.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52