Wherever you have data, you need DataChat
DataChat’s supportive analytics platform and Guided English Language allow you to leverage self-served data analytics and machine learning to uncover sophisticated patterns in your data.
- Collaborate in DataChat by inviting colleagues to a working session, share your work, or post your graphs and narratives to Insight Boards.
- Repeatable workflows will automate your routine tasks and free up your time for more interesting and impactful work.
You can speed up your data science workflows by automating routine model building steps, such as hyperparameter optimization and k-fold Cross Validation, to help you rapidly build and evolve exploratory models.
- The DataChat platform can also be extended with our local instance of your Jupyter notebook and script support.
- Collaborate with your subject matter experts on relevant analyses and conclusions from the same platform.
Leaders and Executives
With DataChat, you can empower your entire organization to give you an advantage over your competition by quickly and confidently making sound, data-driven business decisions.
- Getting to the “Why” quickly with DataChat can help drive growth and reduce costs.
- With DataChat, your team has all the data analytics tools that might seem out-of-reach to them today.
- Your team can collaborate inside DataChat to maximize the overall talent and human resources of the team.
Solutions by Industry
Data is available in companies across all industries and DataChat, combined with business knowledge, can surface meaningful insights to drive decisions. Manufacturing companies are leveraging analytics to identify cost savings, estimate prices more accurately, and optimize delivery processes. In the Retail and Consumer Goods space, companies want to increase revenue and upsell opportunities, optimize store inventory, and explore revenue by channel.
The financial services industry, which includes banking and insurance, is using data to personalize customer experiences and offerings, reduce operating costs, and manage claims and help prevent fraud. In the healthcare and life sciences, organizations are making decisions from increasing staffing efficiency to revenue cycle management to explore bioprocessing data. Your organization can leverage DataChat to answer the questions most critical to your business.
Our customers are reporting direct improvements in efficiency of individuals and teams as well as the benefits of answering the business questions, such as saving money and increasing customer engagement. DataChat can be leveraged effectively across industries in businesses of any scale.
I’ve found the DataChat platform to be the most versatile and intuitive data analytics tool I’ve ever used.
We were constantly trying to make large datasets fit into Excel, which inevitably breaks. But our team isn’t particularly technical…For anything critical we usually just end up hiring a consultant, which is crazy expensive and still pretty slow.
I’ve found the DataChat platform to be the most versatile and intuitive data analytics tool I’ve ever used. …The ability to produce clear models and visualizations within the workflows has been essential in presenting insights and also in displaying real time queries to my team
VP, Keane Consultants
BA Econ. & English
DataChat supports use cases across all industries, here is one showing how a real company applies DataChat to a project.
A Fortune 50 company purchases equipment for their employees in bulk and handles the repair process internally. With data for approximately 200,000 devices over the past five years, the group needed to investigate device lifetime to evaluate a leasing opportunity.
The Supply Chain group independently constructed robust data science pipelines and workflows. They quickly created models that revealed time between device purchase and the first repairs was the primary factor of device life.
The group identified millions of dollars in potential savings by identifying optimal warranty lengths and other lease terms. The group was also able to identify that one particular brand had superior longevity compared to the others, which helped the company promote their ESG goals.