CIO Business Intelligence
JUNE 7, 2022
To ensure robust analysis, data analytics teams leverage a range of data management techniques, including data mining, data cleansing, data transformation, data modeling, and more. What are the four types of data analytics? Data analytics and data science are closely related.
IBM Big Data Hub
SEPTEMBER 19, 2023
To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. And you should have experience working with big data platforms such as Hadoop or Apache Spark. Descriptive analytics: Descriptive analytics evaluates the quantities and qualities of a dataset.
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Domino Data Lab
JANUARY 21, 2021
Producing insights from raw data is a time-consuming process. Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. Results become the basis for understanding the solution space (or, ‘the realm of the possible’) for a given modeling task.
Rocket-Powered Data Science
OCTOBER 6, 2023
The counterexample to the supervised learning explanation of precursor analytics is a “black swan” event – a rare high-impact event that is difficult to predict under normal circumstances – such as the global pandemic, which led to the failure of many predictive models in business. Pay attention!
Jet Global
MAY 1, 2023
Ideally, your primary data source should belong in this group. Modern Data Sources Painlessly connect with modern data such as streaming, search, big data, NoSQL, cloud, document-based sources. Quickly link all your data from Amazon Redshift, MongoDB, Hadoop, Snowflake, Apache Solr, Elasticsearch, Impala, and more.
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