It’s a generic method to explore the Bigdata Knowledge Graph. Ideal if you are implementing an User Interface that only accepts a partial name but no details about the type of Entity. 
from bigdata_client import Bigdata

# Create a Bigdata object, the main entry point to the API
bigdata = Bigdata()
results = bigdata.knowledge_graph.autosuggest("tesla")

for obj in results:
     print(f"{obj.name}: {obj.id}")
As illustrated below, it is possible to easily generate portfolios or interest lists: 
tickers = ["META", "AAPL", "AMZN", "NFLX", "GOOGL"]
FAANG = []
for t in tickers:
    FAANG.append(bigdata.knowledge_graph.autosuggest(t, limit=1))

print(FAANG)
If you know the type of Entity you are looking for, you can use the find_{element}() method.