Knowlegement Management in Opera Solutions

1. Submitted to : Supratik Ghatak
Submitted by: Manmeet Kaur Chatha
Division: C
Roll No: 14
PRN: 15020441139

2. Process followed for the Project
The above project was assigned by the professor and was well researched on the Internet
After careful analysis of the topic assigned, the company (Opera Solutions) was approached and permission to
conduct interview was obtained through email
The questionnaire was prepared for the above topic and emailed to the Interviewer. On the receipt of confirmation of
interview, telephonic interview was conducted for the purpose of completion of the assignment.

3. Opera Solutions
World leader in Big Data &
Analytics
Incorporates science & technology
to provide solutions to their clients
Analyse their client’s future
behaviour and suggest
strategies keeping in
consideration their customer
base

4. Solutions offered by Opera Solutions
Travel
Capital
Markets
Telecom &
Helathcare
Consumer
Banking
Spend
Analytics

5. How is Opera Solutions
Managed?
Opera solutions is
managed by a specialised
Software Team
The Software Team looks
into the development as
well as constant
improvements in the
software
The software is usually
hosted on the servers
which are located in the
US office

6. Who are your Clients?
(The identity of the clients is confidential)
largest pharmacy chain
from US
largest cinema chains of
UK
biggest credit card
companies in US

7. Is there any standard industrial
process/model in use by Opera Solutions?
Opera Solutions is managed by Data Rush Platform (DRP)
DRP is used to build Proprietary Signal Hub Platform (SHP)
SHP is able to process big data using Hadoop efficiently

8. Why Signal Hub
Platform?
It aids the businesses to enhance their ability to create customised and personalized contacts with their
clients.
It further aids the businesses to serve their customers efficiently and save on costs. It is faster and
accessible.
It also aids in the development of Bid Data Analytics in an organization.

9. Components of Signal
Hub Platform
APIs
(Application
Programming
Interface)
Analytics engine
Signal Generator &
Management System
ETL (Extract,
transform &
Load) Processing
Data Filter &
Mapper

10. How the above model has been
implemented?
The model has been implemented
in YAML Language in order to
deliver quicker, faster and accurate
solutions to the client's complex
problems

11. How the implementation of the above model
has benefitted Opera Solutions?
They are able to market themselves uniquely
It has improved visibility and alignment with their clients
ensuring cordial client relationships, responsive to their needs
and solutions requirement.
Through the software, they are able to generate quick & meaningful insights for the
clients

12. What modifications have been effected by
Opera Solutions in the model it has
implemented?
Most of the clients have enormous amount of data so they have integrated various techniques like
parallel processing
The parallel processing incorporates Hadoop clusters to make it more faster
They have also tries to automate the process so that the data that comes on a periodic basis does not
require manual intervention

13. Does the model used by Opera Solutions
responsive to changes in market dynamics?
the software used by the
company is continuously
upgraded to meet the ever
evolving client requirements

14. How the process of up-gradation is done
and how often it is done?
Usually the development team looks into the constant feedback of the product and make the
changes to improve the software
The changes might be adding more functionality, bug fixes, improving performance etc. We usually
release a new version of the software quarterly.

15. How is quality and operational efficiency ensured in
your current model in practice?
• The software is tested by a special testing team which tests the
system in stress scenarios
• Further the development team looks into the quality management
and improvement
• The efficiency of the system is aimed to maintain and managed
continuously.

16. What tools are used for testing the model in
practice?
The server performance is constantly monitored by the IT team checking the spikes in CPU and RAM
usage.
The output of the software is verified by comparing the results with other standard big data tools
like SAS, Python etc.