Database-centric Datasets Relational Database 
Data Engineering Weekly
AUGUST 25, 2024
However, it’s only by combining these with rich proprietary datasets and operational data streams that organizations can find true differentiation. The author writes an overview of the performance implication of disaggregated systems compared to traditional monolithic databases.
Data Science Blog: Data Engineering
NOVEMBER 15, 2023
The database for Process Mining is also establishing itself as an important hub for Data Science and AI applications, as process traces are very granular and informative about what is really going on in the business processes. Note from the author: Although object-centric process mining was introduced by Wil M.P.
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AltexSoft
JUNE 7, 2021
Apache Hadoop is an open-source framework written in Java for distributed storage and processing of huge datasets. Hadoop was created to deal with huge datasets rather than with a large number of files extremely smaller than the default size of 128 MB. The table below summarizes core differences between two platforms in question.
Knowledge Hut
NOVEMBER 17, 2023
The demand for data-related professions, including data engineering, has indeed been on the rise due to the increasing importance of data-driven decision-making in various industries. Becoming an Azure Data Engineer in this data-centric landscape is a promising career choice. Learn how to process and analyze large datasets efficiently.
Rockset
AUGUST 2, 2023
This enrichment data has changing schemas and new data providers are constantly being added to enhance the insights, making it challenging for Windward to support using relational databases with strict schemas. Windward also used specialized databases like Elasticsearch for specific functionality like text search.
Cloudera
NOVEMBER 15, 2021
Structured data can be defined as data that can be stored in relational databases, and unstructured data as everything else. Related to the neglect of data quality, it has been observed that much of the efforts in AI have been model-centric, that is, mostly devoted to developing and improving models , given fixed data sets.
Knowledge Hut
JANUARY 30, 2024
Data extraction is the vital process of retrieving raw data from diverse sources, such as databases, Excel spreadsheets, SaaS platforms, or web scraping efforts. The purpose of data extraction is to transform large, unwieldy datasets into a usable and actionable format. What is data extraction? What is the purpose of extracting data?
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