Why a data science platform? AI deployments have grown by 270% over the past four years. Yet data scientists and machine learning engineers still have a long way to go. According to a 2019 Figure Eight Report about the State of AI and Machine Learning, the laborious task of data preparation continues to be a challenge in almost any data-intensive setting.
The proverbial 80-20 rule has it: data scientists spend 80% of their time on data wrangling. Only 20% of their resources are dedicated to analytics. This includes building machine learning models and performing iterations on their ML models to account for changes in source data and keep the model accurate. Over 62% of the respondents are able to update and maintain their machine learning models only sometimes or never.
Another bottleneck in adopting data science solutions is the communication gap between technical practitioners such as data scientists or machine learning engineers and line-of-business owners. The solution? The report puts it this way:
“It’s clear that people in line-of-business roles and technical practitioners must do more to collaborate. By getting in the same room, the two groups can work to find common ground when it comes to their AI initiatives.”
A Data Science Platform for Collaborative Analytics
To counteract these developments, the data science platform Repods offers an end-to-end analytical data environment. You create a data warehouse in seconds. Processes across the entire data journey are automatable. The data science platform takes over the tasks of data extraction and data preparation, allowing you to focus on what matters most—extracting actionable insights out of your data. Further, the platform allows for multi-level collaboration across company functions. It virtually puts different specialists at different locations in the same room.
Ready to find out more? Download our whitepaper to see how we can help you build a long-term analytics solution for your organization.