Data Quality Assessment Solution
“Bad data costs the US $3.1 trillion per year.”
–Thomas Redman, Harvard Business Review
Understand the questions you can ask of your data, and your probability of success, before you begin a costly and time-consuming analytics project.
Analyze with confidence
Are the answers in your data?
Need to know if your data can support your business objective before you begin further analytical processes?
This targeted analysis gives you the confidence that your data contains the information that describes your target.
What other questions can your data answer?
Have you invested time and resources collecting and formatting data for one objective, all the while wondering if that data could also support the analysis of other targets?
Iris identifies the best target candidates within your data, to help identify what other business questions it can answer.
Information Quality Score – indicates the amount of meaningful information available to build a stable predictor.
Information Consistency Score – indicates whether or not the data can be represented in a single model or needs to be segmented.
An informational blueprint that gives you the context of your data in an assumption-free way.
Identify Meaningful, Irrelevant and Duplicate Data
Central & Alternate Targets – identifies target candidates within a dataset.
Proxies to the Target – identifies columns that have redundant information relevant to the target.
Non-Informative Columns – identifies columns that have no relevant information for any analysis.
Duplicate Columns – identifies columns that contain redundant information.