dotData Insight
AI-Driven Insight Discovery and Business Hypothesis Ideation for Analysts
Unlock Hidden Business Insights from Enterprise Data
dotData Insight, powered by an AI-driven insight discovery engine augmented with GenerativeAI, uncovers business hypotheses beyond apparent data signals. This cutting-edge solution explores millions of potential data signals within intricate enterprise datasets, liberating data analysts, business intelligence professionals, and power users from arduous weeks or months of repetitive trial and error. The result delivers valuable and previously unseen insights that contribute significantly to the user’s business success.
Step 1
Register Business Data
You can directly input your company’s raw business data. The hypothesis-based quantification and data cleaning required by traditional BI is unnecessary.
- Easy drag-and-drop data upload from a local workstation or stored in object storage like S3.
- Automatically infer metadata such as data types and relationships – minimizing your data cleansing efforts.
- Allows you to add and manage semantic information, such as mapping of product codes and product names, as a dictionary to incorporate more domain context into your analysis.
Step 2
Define Business Goals & Discover Key Signals
Select the target column where your business goals are recorded. Then, dotData will automatically discover the conditions that impact your business the most.
- Select a column that records your primary business metric, such as loan default flags, churn flags, sales volume, etc.
- Select all imported tables that you want to associate with the primary metric.
- Run “AI-driven Key Signal Discovery” to automatically identify the dozens of data patterns and signals contributing to key business metrics.
Step 3
Analyze Business Segments
Combine the conditions exemplified by dotData to find the key drivers behind your business goal and key metrics.
- Automatically infer “magic thresholds” determining conditions that maximize (or minimize) your primary metrics.
- Find the best signal combinations by balancing the segment size (the number of samples applicable for the signals) and the improvement rate of business metrics as indicators of importance.
- Real-time visualization of custom metrics for a multifaceted business evaluation
Step 4
Assemble a Business Hypothesis
Relying on the causal hypothesis and numerical information dotData provides, ideate the actions necessary to achieve your business goals.
- Describe business goals and their context in natural language, and have dotData’s generative AI ideate a causal hypothesis for key signals.
- Develop a deeper understanding of the hypotheses by reviewing the visualized numerical information of the key metric distribution of the samples applicable to the key signals.
- Share your key findings and insights with business executives and analytics colleagues with metrics that justify your hypotheses.
Step 5
Create and Export a Scorecard
Score the number of business segment conditions applicable for samples to identify targets for which business actions should be taken.
- Create a scorecard with the number of applicable business segment conditions for each sample as a score.
- Using changes in scores and metrics as a guide, identify targets for which business actions should be executed.
- Export a scorecard to allow business units to interpret and implement business actions.
Product Features
“The biggest problem is that you can’t just throw more bodies at the data. When done manually, it’s just a repetitive, trial-and-error process that takes time.
dotData solves a problem I’ve been trying to solve for 20+ years.”
Karthik Chandrasekhar
SVP Decision Science, Exeter Finance
Business Signals in Hours, not Days
Book a live demo of dotData Insight and see first-hand how powerful, flexible and simple business signal discovery can be.
