Data Science

Algorithmic approaches to extract patterns, insights, and value from data, in a business decision-making context.
The end-to-end pipeline of Data > Modeling > Decisioning > Deployment, when integrated and applied in specific business decision context, can deliver clear and measurable impact both on revenue and cost. Our objective in delivering data science is just that – ensuring measurable business value.

Introduction

Data science involves a plethora of disciplines and expertise areas to produce a holistic, thorough and refined look into raw data. Data scientists must be skilled in everything from data engineering, math, statistics, advanced computing and visualizations to be able to effectively sift through muddled masses of information and communicate only the most vital bits that will help drive innovation and efficiency.

Data scientists also rely heavily on artificial intelligence, especially its subfields of machine learning and deep learning, to create models and make predictions using algorithms and other techniques.

 

 

Our Data Science services

Statistical Programming

Development in SAS, SPSS, R, Python, Julia, and other languages simplifies and enhances statistical analysis. Data scientists can help your company leverage the benefits of statistical programming.

Data Visualization

Data visualization communicates information clearly and efficiently via graphs, plots, and infographics. Expert data visualization designers can help your team make better decisions with data.

Data Pipelines

Data pipelines are the critical infrastructure that unlock timely analyses, from regular reporting to ad-hoc modeling. Data scientists can help you better gather, unify, and structure data from multiple sources to support your company’s analytics.

Predictive Analytics

Data science, advanced analytics, and machine learning techniques are key to creating predictive models. Developers can work with your team to improve forecasting, customer classification, and many other activities.

Machine Learning

Machine learning (ML) enables computers to “learn” through data without explicit programming. Data scientists can create deep learning algorithms using techniques borrowed from ML, helping your company explore ways to improve operations through real-time data.

Natural Language Processing

NLP enables computers to effectively process large amounts of natural, human language. Whether through voice or text data, NLP specialists can help your company employ language data for processing and sentiment analysis.

What can Data Science be used for?

Anomaly detection (fraud, disease, crime, etc.)
Automation and decision-making (background checks, credit worthiness, etc.)
Classifications (in an email server, this could mean classifying emails as “important” or “junk”)
Forecasting (sales, revenue and customer retention)

Pattern detection (weather patterns, financial market patterns, etc.)
Recognition (facial, voice, text, etc.)
Recommendations (based on learned preferences, recommendation engines can refer you to movies, restaurants and books you may like)

 

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