Actian
OCTOBER 21, 2019
With this release, Actian Avalanche is now available on Microsoft Azure, AWS, and on-premises, delivering on our hybrid and multi-cloud vision. This is particularly appealing to those customers who have large amounts of data which is growing quickly but may not need compute to scale at the same pace.
Smart Data Collective
AUGUST 11, 2022
While different metrics can be used to determine data quality, accuracy is the primary focus since it is easy to change for different data sets and concerns for decision-makers. Data quality is crucial in Artificial Intelligence and automated decision-making. Conclusion.
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Bridging the Gap
SEPTEMBER 7, 2023
This specification might also be referred to as a business case or a vision document, or a business requirements document, although in practice, VRDs typically include many additional sections that would include functional requirements. There are a few common types of data requirements documentation.
Juice Analytics
MARCH 11, 2021
The right product manager We’ve helped launch data products in many industries including healthcare, education, insurance, advertising and market research. In our experience, the recipe for building a successful data product is dependent on a number of specialized roles. Our clients bring the product vision; we make it happen.
Netmind
MARCH 9, 2021
I also want to relate it to the traditional pyramid of knowledge management, DIKW (data, information, knowledge, and wisdom). Although there are some discrepancies on the model’s limits and specific definitions, I wanted to give you my vision from a practical and usable point of view. How do we ensure good data governance?
Astera
MAY 9, 2023
AI addresses this challenge by using Natural Language Processing (NLP) that recognizes patterns in language and identifies relevant keywords and phrases to extract information from unstructured data sources. AI also uses computer vision to extract data from images and videos.
Netmind
NOVEMBER 1, 2020
I also want to relate it to the traditional pyramid of knowledge management, DIKW (data, information, knowledge, and wisdom). Although there are some discrepancies on the model’s limits and specific definitions, I wanted to give you my vision from a practical and usable point of view. How do we ensure good data governance?
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