A data science service for smart business insight
Data science is becoming more and more important in different domains such as e-commerce, healthcare, smart energy, business, social media, insurance, and research & development, to name a few.
Data science projects require multiple competences such as programming, statistical and analytical skills as well as project management and communication. Initiating a project would mean evaluating several requirement, such as: Does your project have small, large or big data? Do you anticipate that the data are growing in the nearby future? Are real-time analytics needed? To what degree should the analytics be automated?
A project can often be captured with the following flow-chart:
Data science projects require multiple competences such as programming, statistical and analytical skills as well as project management and communication. Initiating a project would mean evaluating several requirement, such as: Does your project have small, large or big data? Do you anticipate that the data are growing in the nearby future? Are real-time analytics needed? To what degree should the analytics be automated?
A project can often be captured with the following flow-chart:
A few examples of services provided:
- Sales volume forecasting using machine learning
- Deployment of dashboards
- Webscraping
- Natural language processing (NLP)
- Computer vision
- Sentiment analysis
Make your dashboards come true
Dashboards are an excellent way to provide real-time insight in sales, stock, forecasts etc. Dashboards can be customized to your specific needs. The preparation of a dashboard takes between 2 and 8 weeks. Check for prices here.
A dashboard demo, try it yourself at https://rrighart.pythonanywhere.com
Data science toolbox
A list of tools used in previous projects. Of course, every project is unique with its specific needs, and new innovative tools appear rapidly. Please feel free to suggest your own tools.
Activity |
Tool |
Analytics |
Python, R, Matlab |
Machine learning |
Scikit-learn, Caret, Keras, AWS forecast, IBM SPSS |
Large, big data and ETL |
Spark, Dask, H2O, SQL |
Visualization |
Plotly, Matplotlib, Bokeh, GGplot, Seaborn |
Dashboards |
Dash, Shiny, Klipfolio, Tableau, Grafana |
Cloud |
Amazon Webservices (AWS), Google cloud, Hidora |
OS & software platforms |
Linux, Docker, GitHub |
Communication |
Jupyter notebook, R Studio |
Email: rrighart@googlemail.com
Images were taken from Unsplash and credits go to the following persons:
