What is DataChat?
DataChat is a built-from-scratch analytics platform that presents data in a natural, familiar, spreadsheet setting. Of course these spreadsheets can be large and have millions or billions of rows, and the user can carry out rich data science and data engineering tasks by simply using an intuitive point-and-click interface. Rather than learning and perfecting how to write complex code in programming languages like Python and SQL code, users now use a data-centric, visually intuitive, way to carry out these tasks. This aspect of DataChat allows an individual to upskill their data science game quickly.
Behind the scene is a novel declarative, natural, and comprehensive no-code language called DataChat Guided English Language (GEL©). All user requests translate into this language which has the syntax of English. Thus, all activity can be captured as a sequence of sentences in DataChat GEL, and this paradigm then forms the basis for reproducibility, collaboration, transparency, and interfacing with other platforms. This aspect of DataChat allows the organization to govern artifacts (models, charts, reports, etc.) that are created in the platform, and also allows for seamless collaboration allowing an organization to realize the full potential of their collective team.
DataChat’s GEL puts powerful data engineering, wrangling, and preparation at everyone’s fingertips.
- Fill in missing values, calculate averages, create pivot tables, and more quickly and easily without complicated formulas or interfaces.
- Built-in annotation support helps make even the most complex dataset easy to understand and engineer.
- GEL also created replayable and shareable workflows that enhance transparency and trust by creating an easy-to-follow record for every data product, including machine learning models.
Automated analytics and visualizations help provide intuitive, statistical summaries of your data and simplify the data exploration process.
- Help discover trends and insights quicker than ever before.
- Leverage workflows to automate routine work from engineering to discovery.
Machine learning tools support every user, from the business user to the data scientist.
- Helps uncover interesting patterns in your data.
- Automatically optimizes complicated machine learning concepts such as cross-training and cross-validating several models, so you don’t have to.
- Automated for routine functions, saving time for data teams.
GEL enables collaboration and co-creation across functions, while Insights Boards and workflows give visualizations and other narratives a shared space that encourages discussion.
- Enables real-time collaboration, co-creation, and iteration across teams and departments.
- Insights Boards and Workflows give visualizations and other narratives a shared space that encourages discussion.
Modern SaaS Deployment
DataChat’s state-of-the-art, secure SaaS platform supports multiple authentication methods.
- Database processing allows for efficient, scalable work with very large datasets.
- Rich database connection support for all major database systems, including : Snowflake, BigQuery, PostgreSQL, Redshift, SQL Server, MongoDB, and more.
What is Data Science?
Data science is the study of applied mathematics, statistics, and scientific principles to extract information and insights from large sources of data.
What is Data Analytics?
Data analytics involves using the information and insights drawn using data science to aid in business decision-making and provide actionable solutions to business issues.