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Business Metadata

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Segments

In the real world when you work with the data you need to have a better understanding of the data and at the same time, data quality should also be contemplated. Without these, you will end up with inaccurate insights.  

Using Business Metadata you will be able to easily understand the data where the detailed description will be given by the respective owner. Also, quality checks will be done by the multiple teams and provide the signoff. This way maintaining the Business Metadata on the sprinkle resources will set the standardization on the resources.

Setting up Business Metadata 

Users with Admin access will create the Business Metadata. Click on Business Metadata under the Admin section. You can create a new Business Metadata by clicking on the ‘New’ button.



After clicking on the ‘New’ button give a Name and Description to the Business Metadata. 


Add Attributes in the Business Metadata

Now inside the Business Metadata click on “Add Metadata Attribute”. Give a Name, Description, and select the Type (data type) of the attribute. At last, you can select the Applicable Entities of the Attribute and save.


The following example will explain all the fields in the attribute. 

Giving Name as “Data Validation”. Description as “Data Validation is done by Data Team”. This attribute tells whether data is validated by the Data team or not. So, here the Type should be Boolean. And Data Validation should be done through the pipeline that is from data ingestion to reports. So, Applicable Entities (Applicable Sprinkle resources) are selected under this attribute.


Now, this Metadata can be added to the sprinkle resources. Based on the metadata the end-users can decide whether the data can be consumed or not.

To add Business Metadata and its attribute, the resource owner should click on the Metadata and then click on Set Attribute. Post that select the Business Metadata, Attribute and give the Value in it. Based on the value the end user will decide whether to consume the resource or not. 


import requests
from requests.auth import HTTPBasicAuth

auth =  HTTPBasicAuth(<API_KEY>, <API_SECRET>)
response = requests.get("https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE_ID>", auth)

print(response.content)

library('httr')

username = '<API KEY>'
password = '<API SECRET>'

temp = GET("https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE ID>",
           authenticate(username,password, type = "basic"))

temp = content(temp, 'text')
temp = textConnection(temp)
temp = read.csv(temp)

/*Download the Data*/

filename resp temp;
proc http
url="https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE ID>"
   method= "GET"  
   WEBUSERNAME = "<API KEY>"
   WEBPASSWORD = "<API SECRET>"
   out=resp;
run;

/*Import the data in to csv dataset*/
proc import
   file=resp
   out=csvresp
   dbms=csv;
run;

/*Print the data */
PROC PRINT DATA=csvresp;
RUN;

import requests
import json

url='http://hostname/api/v0.4/createCSV'

username='API_KEY'
password='API_SECRET'

files={'file':open('FILE_PATH.csv','rb')}
values={'projectname':PROJECT_NAME','name':'CSV_DATASOURCE_NAME'}

r=requests.post(url, files=files, data=values, auth=(username,password))

res_json=json.loads(r.text)

print(res_json['success'])

import requests
import json

url='http://hostname/api/v0.4/updateCSV'

username='API_KEY'
password='API_SECRET'

files={'file':open('FILE_PATH.csv','rb')}
values={'projectname':PROJECT_NAME','name':'CSV_DATASOURCE_NAME'}

r=requests.post(url, files=files, data=values, auth=(username,password))

res_json=json.loads(r.text)

print(res_json['success'])

import requests

url='https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE ID>'

username='API_KEY'
password='API_SECRET'

r=requests.get(url,auth=(username,password))
print(r)
print(r.text)

import requests
import pandas as pd

url='https://<hostname>/api/v0.4/explores/infoByFolder/<SPACE_ID>'

username='API_KEY'
password='API_SECRET'

r=requests.get(url,auth=(username,password)).json()
df = pd.DataFrame(r)
print(df)

import requests
import pandas as pd

url='https://<hostname>/api/v0.4/folders/byOrgName/<ORG_NAME>'

username='API_KEY'
password='API_SECRET'

r=requests.get(url,auth=(username,password)).json()
df = pd.DataFrame(r)
print(df.loc[:,['name','id']])

import requests

import pandas as pd

import io

url='https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE ID>'

secret='API_SECRET'

r=requests.get(url,headers = {'Authorization': 'SprinkleUserKeys ' +secret } )

df = pd.read_csv(io.StringIO(r.text),sep=',')

import requests

import pandas as pd

import io

url='https://<hostname>/api/v0.4/segment/streamresult/<SEGMENT ID>'

secret='API_SECRET'

r=requests.get(url,headers = {'Authorization': 'SprinkleUserKeys ' +secret } )

df = pd.read_csv(io.StringIO(r.text),sep=',')

import requests

import json

url='http://hostname/api/v.o4/createCSV'

files={'file':open('path/file.csv’')}

values={'projectname':PROJECT_NAME,'name':'csv_datasource_name/table_name'}

secret='API_SECRET'

r=requests.post(url, files=files, data=values, headers = {'Authorization': 'SprinkleUserKeys ' +secret } )

res_json=json.loads(r.text)

import requests

import json

url='http://hostname/api/v.o4/updateCSV'

files={'file':open('path/file.csv’')}

values={'projectname':PROJECT_NAME,'name':'csv_datasource_name/table_name'}

secret='API_SECRET'

r=requests.post(url, files=files, data=values,headers = {'Authorization': 'SprinkleUserKeys ' +secret } )

res_json=json.loads(r.text)