Backgrounds:
KDB+ is widely used in Financial industry and others. It is inmemory, column based, efficient especially procient tp process Financial data set. Many investbanks, hedged funds and proptrading hours emploited KDB+ to many data analytics and data services. KDB+ play a significant role in analysis in back testing and daily trading, find out root cause and improve trading quality and efficiency.?Python is also widely used in Finiancial industry and it can manipulte KDB+ easily, provide many libs to do analysis.
In this course, will introduce how Q/KDB+/Python are used in Financial industries(how to store data, how is the data API used, how is gateway exploited to support concurrent connnections, trouble shooting and??support on KDB+ and etc) and many senarios and relevant solutions.
What's the advantage of KDB+ in financial analysis?
Senarios
Performance & Efficiency
which kind of financial dataset
KDB+ fundamentals
type definiation & cast
functional select/update/delete
functions/lamda, sync/async function invocation
web socket support
file compression
sym enumeration and denumeration
splay table and partition
How can we deploy KDB+
tickplant
RDB/HDB
gateway/API
Reporting
How can we access KDB+
Q
Python
R
Java
C/C++
How can import data from other data source into KDB+?
txt/csv
html/web page
SQL Server | 
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shuhaipeixun
1299983702
總部李老師
