Code-free Data Science

There will always be a plentiful supply of data scientists on-hand to perform hand-cut custom data science. For what most businesses requirements, the typical data scientist is over-skilled. Only other data scientists can understand their work and, importantly, only other data scientists can check their work.

What businesses require for most tasks are people with the data-engineering skills of data scientists and not necessarily their statistical skills or their understanding of a scientific-method of analysis.

Data engineering on a big scale is fraught with challenges. While Excel and Google Sheets can handle relatively large (~1mn row) datasets there is not really a similar software solution that allows easy visualization and manipulation of larger data sets. NoSQL / SQL-databases are required for super-scale data engineering, but this requires skills of the super-user. As ‘data-is-the-new-oil’ mantra makes its way into businesses, people will become exposed to a growing number datasets that are beyond the realm of the software available to them and, potentially, their skill sets.

At Knowledge Leaps we are building a platform solution for this future audience and these future use-cases.The core of the platform are two important features: Visual Data Engineering pipelines and Code-Free Data Science.

The applications of these features are endless; from building a customer data lake, or building a custom-data-pipeline for report generation or even creating simple-to-evaluate predictive models.

Platforms In Data

Data-is-the-new-oil is a useful framework for describing one of the use-cases we are developing our platform for.

Rather than their being just one platform in the create-process-deliver-use data analytics pipeline, a number of different platforms are required. The reason we don’t fill our cars up with gasoline at our local oil rig is the same reason why data distribution requires a number of different platforms.

Data Platforms

The Knowledge Leaps platform is designed to take raw data from our providers, process and merge these different data feeds before delivering to our customers internal data platforms. Just like an oil-refinery produces the various distillates of crude-oil, the Knowledge Leaps platform can produce many different data products from single or multiple data feeds.

Using a simple UI, we can customize the processing of raw data to maximize the value of the raw data to providers as well as its usefulness to users of the data products we produce.