SDMX API Data analysis and Visualization
Budget: $30 – $250 USD
Develop a 'template' and methodology to review and understand the structure, content and relationships of selected datasets that will be input into a prototype, including:
Document data types, length and codes or patterns
Collect descriptive statistics like min, max, count and sum.
Tagging data with keywords, descriptions or categories.
Performing data quality checks
Validate the feasibility / challenges of joining with other datasets
Discovering metadata and assessing its accuracy.
Identifying key candidates and foreign-key candidates
Identifying value dependencies, consistency rules, aggregation rules, etc,
So i need all this documented in a dedicated git repository, where i can manage:
Documentation (Wiki, Readme, etc)
Datasets (csv files, etc)
Notebooks with data profiling analyses (e.g., jupyter notebooks)
What i am trying to achieve
Get data from SDMX multiple API endpoints, data that are closely related
Combine these data into one schema that can easily be analyzed, queried, and shared
The final code should be self-documented
Document data types, length and codes or patterns
Collect descriptive statistics like min, max, count and sum.
Tagging data with keywords, descriptions or categories.
Performing data quality checks
Validate the feasibility / challenges of joining with other datasets
Discovering metadata and assessing its accuracy.
Identifying key candidates and foreign-key candidates
Identifying value dependencies, consistency rules, aggregation rules, etc,
So i need all this documented in a dedicated git repository, where i can manage:
Documentation (Wiki, Readme, etc)
Datasets (csv files, etc)
Notebooks with data profiling analyses (e.g., jupyter notebooks)
What i am trying to achieve
Get data from SDMX multiple API endpoints, data that are closely related
Combine these data into one schema that can easily be analyzed, queried, and shared
The final code should be self-documented