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Data Science

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What we do ?

We offer custom made decision engine solutions to small, mid-size and large enterprises

What you need to do

This form is an initial process to understand your data needs. You may keep your answers short and simple at this point.

Problem Definition

  • Think of terms of the end-user.
  • State one problem at a time and repeat this process as needed.
  • What decisions do you need to make ?
  • What is your tolerance to uncertainty ?
  • State a few important details

Data Gathering

Sources

Thinking through what data is needed and choosing the best ways to obtain it, whether it’s querying internal databases, or purchasing external datasets.

Structured, Unstructured, both

Structured data is clearly defined and searchable types of data, while unstructured data is usually stored in its native format. Structured data is quantitative, while unstructured data is qualitative. Structured data is easy to search and analyze, while unstructured data requires more work to process and understand.

Data Retrieval Methods

Data feeds, API, Data scraping, Survey data, databases, image captures

Data Access requirements

Understanding how to access the data needed is crucial to start the work. This part requires lots of expertise and experience in working on multiple platforms.

Data Cleaning

  • Is your data set complete?
  • Would you merge data sets
  • How would you treat missing values?
  • Do you need to standardize data?
  • Do you need to normalize data?

Data Exploration

  • Do you know what data is important for your analysis?
  • Do you know if there is redundant data?
  • Are you aware of data ranges and typical distribution?
  • Do you know the different types of data?
  • Are you exploring a small or large number of variables?

Modeling

  • What’s more important accuracy or ability to interpret?
  • What’s more important prediction or benchmarking?
  • Are you concerned about prediction and confidence intervals?

Testing

  • Is your data Time-Series based?
  • Do you know if there is redundant data?
  • Do you have a large set of data or small?
  • Do you want to compare a model with previous models?
  • Do you want to be able to modify models at your disposal and test them?

Deployment

  • Do you need web-based deployment?
  • Do you need automated decisioning?
  • Do you need decision model integration?
  • Do you need to view historical data performance?

Control

  • Do you need a warning system?
  • Do you have process expectations?
  • Do you need a list of actionable items?

Repeat

  • How often do you expect to tune up the system?
  • Do you want this process to be automated?
  • If supervised, do you want to act independently?

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