Data Dictionary

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32 comments

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    Ishwar Nataraj

    The rest API's still work with 7x versions and higher. This can be embedded into a web app after figuring out which cube the rest api should work on. In the following example, I am generating a html table for getting the metadata of the cube:

    import requests
    import pandas as pd
    import json
    from pandas.io.json import json_normalize

    url = "http://localhost:8081/api/elasticubes/metadata/TESTCUBE/fields?count=100"

    payload = "<file contents here>"
    headers = {
    'authorization': 'Bearer XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
    'Content-Type': 'text/plain'
    }

    response = requests.request("GET", url, headers=headers, data = payload)

    val = response.text.encode('utf8')
    data = json.loads(val)
    df = pd.DataFrame(json_normalize(data))
    print(df.to_html())

     

    You can take the response and plug it into a web app like a react js app to generate the table and add a javascript to download the details into a excel file.

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    Hamza Jap-Tjong

    What I did myself, was downloading the Sisense MongoDB connector and connect it to the Sisense application DB. Import it into an EC and design a dashboard on top of it. 

    It now automatically import all EC-data; Source, Tables, Fields, Descriptions etc.

     

    Keeping everything up to date in the web EC-manager will also keep your dashboard up to date.

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