Data Analytics

In Japan, it is said that many companies are even not aware of the data that they collect and 40% of the data lies unused. Retail, insurance, healthcare, banking, manufacturing are few areas with huge sets of data. With the advent of analytics and machine learning or processing tools, data analytics is a growing area for partnership between client and Fidel.

Database : SqlServer, mongoDB, mySql, Oracle

Languages : python

Reporting Tools : PowerBI, Tableau, Crystal Reports

Other : Speech to text and other home-grown tools, TensorFlow


Fidel works with clients in various areas –

a. Data identification and cleansing –

Fidel works with users in various departments, identifies data sources and then works with the client to identify key data, clean it and put it together in a database or repository.
Fidel primarily dispatches bilingual BAs and engineers onsite to the client premises and ensures security, privacy and quality.

b. Data modelling and analytics –

Fidel works with clients in identifying some key impact areas and then starts working on the data. In past, Fidel has dispatched data scientists at client site to model on the data and work on an iterative basis towards the goal.

c. Reporting –

Fidel has engineers with PowerBI or other tools experience and works with clients to develop reports and maintain the same on an ongoing basis. PowerBI, Domo, Tableau are few reporting software that Fidel has worked in past.

d. Vernacular data creation –

Fidel works with companies with chatbots or AI engines and helps them to create data to train the engines. Fidel has access to Japanese data and other ASEAN or South Asian languages. The data is further transcripted and annotated to deliver in a particular format.

e. Sentiment analysis –

Fidel works with clients in the areas of sentiment analysis. Companies often want to finetune its operations by implementing client feedback across business process improvements. For this, client call center data is taken up for analysis, transcripted and then analyzed for sentiments so that clients understand the pain or frustration points of clients while using the website or a particular service. This analysis is used to further finetune operations and reduce the pain points.

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