Golang for Data Analytics
                     Golang for 
Data 
Analytics
Introduction
• Organizations collect vast 
amounts of data.
•  This mass of data tell facts that 
are relevant for key decision 
making.
• Data insights help businesses 
understand challenges and devise 
solutions.
• Due to this, demand for Data 
Analytics applications is on the 
rise.
Golang
• Golang is a modern 
language which is 
procedural, imperative 
and modular. 
• Google’s Golang helps 
build scalable and 
efficient solutions. 
• Go is suitable fit for Data 
Analytics solutions and 
at every step of the data 
analytics process.
Data Gathering
• Data Analytics application should be able to collect and 
store vast amounts of error free data that takes into 
account logical, cost and privacy considerations. 
• It should also be able to store incoming data that can be 
modeled and reported while also joining data from 
multiple sources in a logical manner.
• There are many Databases in Golang such as InfluxDB, 
Minio, CokroachDB. Go has several APIs for all of the 
commonly used datastores such as Mongo and Postgres. 
This kind of resource backup makes it easy for Golang Data 
Analytics applications to collect and organize data.
Processing and 
Analyzing Data Sets
• The next step is to Process data sets to clean up messy raw 
data. 
• Algorithms are applied to build and validate data models 
while performing machine learning/ deep learning.
• In Go the gonum organization powers data science 
computations by providing numerical functionality. Floats, 
Matrix, Stats, gograph are Golang projects related to data 
analytics, statistics and arithmetic. 
• They help develop arithmetically sound and comprehensive 
Data Analytics applications.
Visualizing and 
Communicating Results
• Good data visualization of results means sound decision 
making by users. 
• Application should convey results of investigation in a way 
that makes sense and can be easily communicated. 
• Golang projects such as gophernotes, dashing-go and 
gonum plotting make it easy to create powerful 
visualizations. Creating Custom APIs for this purpose and 
utilizing resources such as D3 contribute to the 
comprehensiveness of Golang Data Analytics applications.
• At Gowitek we have worked on several Data 
Analytics projects spanning industries such as 
Agriculture, Manufacturing, Healthcare, Retail and 
Conclusion more. 
• Scalable and efficient Data Analytics 
solutions strongly support business goals and solve 
core challenges.