Rocket-Powered Data Science
JULY 6, 2021
Specifically, in the modern era of massive data collections and exploding content repositories, we can no longer simply rely on keyword searches to be sufficient. Labeling, indexing, ease of discovery, and ease of access are essential if end-users are to find and benefit from the collection. Data catalogs are very useful and important.
IBM Big Data Hub
APRIL 15, 2024
For example, as manufacturers, we create a knowledge base, but no one can find anything without spending hours searching and browsing through the contents. Or we create a data lake, which quickly degenerates to a data swamp. Contextual data understanding Data systems often cause major problems in manufacturing firms.
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datapine
NOVEMBER 19, 2019
In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data discovery tools available in the market to take their brand forward.
Domino Data Lab
JUNE 15, 2021
Over the next decade, the companies that will beat competitors will be “model-driven” businesses. These companies often undertake large data science efforts in order to shift from “data-driven” to “model-driven” operations, and to provide model-underpinned insights to the business. Why Snowflake UDFs.
datapine
NOVEMBER 19, 2019
In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data Discovery tools available in the market to take their brand forward.
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