McMarvin
Data Science Services

Improve your business performance by unlocking the value of Data Science


Analyze your data to improve business outcomes

Redefine your business Strategies and Increase the competitiveness of your business by improving your products & services with Data Science.

Data is the core of your business, and analytics lets you know how well things are going on and examine what is working effectively for the business and what isn’t. In today’s era, successful companies are growing more because they utilize their data towards gaining insights to deliver better products and services to their clientele.

Many companies are still struggling towards using their data more efficiently, as it is not organized and troublesome to manage. Their workflow & process still lack the necessary insights they need to extract to make essential business decisions. So, we’re here to help you out and deliver customized business solutions, specially curated for your business.

What is Data Science?

Data Science is a technology that adopts scientific processes and algorithms to draw out knowledge and insights from the data.

Why Your Business Needs Data Science Services?

Data science uses scientific methods, processes, algorithms, and systems to extract knowledge from data and leveraging this data to make significant decisions is an essential strategic practice for any business. Investing in a data science expert or data science technology can begin to add value to your business in these meaningful ways:

Improving Product Relevance
Data Science can explore historicals, analyze the market, and make comparisons to the competition. This can help in understanding the usefulness of the products. Using data science, one can have a deep understanding of the market’s response to the company’s product.

Staff Training
Data Science can give insights and knowledge about the company to the employees. These insights can be used to populate online knowledge base software that holds essential experience for employees.

Finding Target Audience
The companies collect customer information like website visits, social media likes, and email surveys. By using data science with this collected information, any company can generate insights to target the audience more effectively. This means you can tailor products and services to particular groups of customers.

Benefits of Data Science Services

With the help of data science services, the developed products can be delivered at the right place and at the right time. Data science helps business organizations in knowing when and where their products sell best.


  • Data Science helps the marketing and sales team of various organizations to understand their audience.

  • Our data scientists allow companies to make smarter business decisions which lead to higher profit and improved efficiency.

  • With data science services, it is comparatively easier to sort data and look for the best candidates for an organization.

  • Data Science is versatile. It can be used in any field to get better and faster results.


Use Cases of Data Science In Real World

Airbnb:

  • Data Science plays an essential role in Airbnb. This company uses data to provide better search results to its clients. Airbnb uses demographic analytics to analyze bounce rates from their websites.



Facebook:

  • With millions of users in the world, Facebook uses data science for a large scale quantitative research to gain insights into its customers’ social interactions. Facebook uses the advanced technology of data science called deep learning.



Uber:

  • Uber uses data science to calculate its surge pricing. When there is more demand for rides, the price of the trip goes up. This happens when drivers are scarce. However, when the need for rides is less, the cost of the ride is lower. This dynamic pricing is rooted in done through Big Data and data science to calculate fares of the trips based on the parameters.



McMarvin Data Science Process

What McMarvin offers in Data Science?

1. Predictive Modeling:

● Churn prediction
(Retail, manufacturing, Job Industry)

● Device failure & breakdown prediction
(Oil & Gas Industry)

● Match winner, Score prediction
(Sports Industry)
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2. Recommendation System:

● Product recommendation to customer:- collaborative filtering and content-based filtering
(E-commerce industry)

● Recommendation to traveller
(Tourism industry)

● Recommendation to customer
(Restaurant, hotel etc industry)

3. Text Analytics:


● Text insights

● Document scanner and extractor

● Automatic summarization

4. HR industry, Digital marketing etc..
--

Our Data Science Process


The data science process is an iterative data science methodology that helps in delivering intelligent applications and predictive analytics solutions. The data science process has a few significant stages that can help in executing the outcome of the projects:

Business Understanding:

  • The first step is understanding the business and business needs so that we can extract useful data and start working on it.

Data Acquisition and Understanding:

  • After getting the idea about the business, the next step is to understand each part of the data.

Modeling:

  • In this stage, the data scientists analyze the data and creates a model that best fits the company’s data.

Deployment:

  • After the modeling of the data is done, it has been shared with the company’s executives who can take further actions.

Customer Acceptance:

  • Here, the customers accept the data science process created for them and get familiar with it.

Tools & Technologies We Use





ElasticSearch Kibana


  • It is an open-source and default data visualization platform for Elasticsearch. Using Kibana, we can search, interact, and view the data stored in kibana.



TensorFlow

  • It is an open-source software library for data flow across a range of tasks.
    •



Python

  • It is a high-level, interpreted, and general-purpose programming language.



Keras

  • It is an open-source neural network library. Keras is a high level neural networks API, Capable of running on top of Tensorflow, CNTK, And Theano.

    McMarvin researchers use Keras for fast prototyping.



Scikit Learn

  • It is the most useful machine learning library in Python. Scikit Learn consists of a lot of valuable tools for statistical modeling and machine learning.

    Scikit-Learn is a library for machine learning problems and combined with EDA libraries like Pandas, Numpy and Matplotlib for analysis and visualization.



Spacy

  • It is an open-source software library for Natural Language Processing.

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