Difference between revisions of "Data Interoperability"
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* [[Creatives#Wes McKinney |Wes McKinney]] | * [[Creatives#Wes McKinney |Wes McKinney]] | ||
| − | a cross-language [[development]] platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient [[Analytics | analytic]] operations on modern hardware. It also provides computational libraries and zero-copy streaming messaging and interprocess [[Agents#Communication | communication]]. Languages currently supported include [[Other Coding options#C/C++ | C/C++]], C#, [[Other Coding options#Go | Go]], [[Other Coding options#Java | Java]], [[JavaScript]], MATLAB, [[Python]], [[R Project]], Ruby, and Rust. | + | a cross-language [[development]] platform for in-[[memory]] data. It specifies a standardized language-independent columnar [[memory]] format for flat and hierarchical data, organized for efficient [[Analytics | analytic]] operations on modern hardware. It also provides computational libraries and zero-copy streaming messaging and interprocess [[Agents#Communication | communication]]. Languages currently supported include [[Other Coding options#C/C++ | C/C++]], C#, [[Other Coding options#Go | Go]], [[Other Coding options#Java | Java]], [[JavaScript]], MATLAB, [[Python]], [[R Project]], Ruby, and Rust. |
<youtube>7HiwzHWiF20</youtube> | <youtube>7HiwzHWiF20</youtube> | ||
Latest revision as of 22:40, 2 March 2024
YouTube ... Quora ...Google search ...Google News ...Bing News
- Data Science ... Governance ... Preprocessing ... Exploration ... Interoperability ... Master Data Management (MDM) ... Bias and Variances ... Benchmarks ... Datasets
- Data Quality ...validity, accuracy, cleaning, completeness, consistency, encoding, padding, augmentation, labeling, auto-tagging, normalization, standardization, and imbalanced data
- Apache Arrow
- Pandas provides an efficient implementation of a DataFrame
- Wes McKinney
a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. It also provides computational libraries and zero-copy streaming messaging and interprocess communication. Languages currently supported include C/C++, C#, Go, Java, JavaScript, MATLAB, Python, R Project, Ruby, and Rust.
