More than 80% of a data scientist’s time is spent on preparing data manually. While this is a good sign, considering that as good data goes into building the predictive model, the accurate gets the output.
But, data scientists should ideally be spending more of their time interacting with data, running advanced analytics, training and evaluating the right model, and deploying to production. Today, only 20% of the time goes into the major chunk of that process.
In order to overcome time constraints, companies need to reduce the time taken on cleansing and enriching the data by leveraging solutions for data engineering and preparation.
Most machine learning platform out there today focus 90% of their platform on helping businesses train and deploy model meanwhile without a good data, the deployed model is just as bad as not deploying it at all.
Garbage in, Garbage out
If you are new to data science, you need to understand that “garbage in, garbage out” applies to machine learning in data science.
The accuracy of your machine learning model is directly related to the cleanliness of the data it trained on.
Let me give you an example:
The image below contains historical data retrieved from a well established e-commerce business and we tried using it to train a machine learning model to see what the accuracy will be.
Scope of work is to build a machine learning prediction model that will enable the e-commerce company to categorise a transaction as fraudulent or safe.
Below is the result of the training:
Here we can see that everything about this model is just bad. The accuracy, the Top importance, Coefs etc and that’s because the data we feed the algorithm with is unprepared and need some transformation, i.e the IP address needs to be transformed into countries and so much more.
This is the part where data transformation comes in
This is not a task you want to leave to highly paid, hard-to-find data scientist experts and that’s why we’re building this feature into our data science https://voyancehq.com/#omni-platform platform.
Machine learning ready data
If your company is looking to use data science to solve their problems or augment business process, you must allocate time and resources needed to clean data before building a machine learning model.
This is where Voyance can help with our transformation feature using our data science platform and in-house data analyst.
Voyance is a full-service data science team for startups and organisations of any size.
We take care of all your data needs at every step along your journey, from delivering insights and predictions using our OMNI platform and to setting up a scalable data infrastructure to empower you to answer any data question you might have.
Sign up for a free 30-minute chat with a senior data scientist here: https://calendly.com/voyance or visit our website to learn more https://voyancehq.com
