Did you want to discover not-yet-known errors in your data?
Did you want to discover issues before they cause incidents?
Has your list of business rules to control data quality become too large?
Your business analysts can't keep business rules up-to-date?
Tell us your story
What is a business data?
"Hm. I have data, but what do you call a business data?"
Business data is a data that describes the activity of any business: sales, financial transactions or data about customers, assets, products, contracts.
Why do I need help?
"But my business data seem to be ok. I don’t think I need any help."
You must be lucky then. Or you spend a fortune to keep your data in a good state. Or maybe you are one of that 60% of businesses that do not measure the financial impact of poor data quality?
The data quality comes at a price
"True, we spend quite a lot of effort to maintain data quality."
You are not alone, on average, companies waste 50% of the time of their data analysts finding and correcting errors. This time could be spent elsewhere or not spent at all!
How we can help to save costs
"Are you saying dataright could help to avoid these spends? But how?"
Our product is a zero maintenance (well, almost) deploy-and-forget solution. It can be used in a range of ways: from one-off analysis of some particular dataset all the way to fully unsupervised Data Quality assurance system.
How exactly our product saves costs
"Ok, but how exactly does that saves costs to a business?"
It saves costs in 3 ways:
- by automating issue discovery process hence saving resources on developing traditional BI reports/rules used by business analysts to find issues
- by automating issue investigation and saving manual efforts of data analysts in a search for fixes for each particular issue
- by discovering errors in data that are not yet known to your business analysts before they cause incidents and preventing potential financial and reputational losses before they happen
Not just anomaly detection
"Does it have anything to do with anomalies? I think I’ve heard that term before"
Yes, there are other offerings on the market that claim they do anomaly detection in data. At DataRight we don’t use term anomaly, because it is too shallow. It only means that something isn’t right with the data. We go much further, we say what exactly not right with data and how to make it right. It is a critical feature that makes us different and enables us to build fully automated Enterprise Data Quality solutions.
Every data is unique
"Oh, interesting! But my data is very unique."
Our models are not specific to any particular business or industry. They need any business data to work, the more, the better.
No up-to-date documentation
"No, I meant to say, our documentation isn’t up to date."
Our machine learning models and algorithms don’t need any documentation at all. They only need your actual data.
self adjusting algorithms
"What if my business process changes?"
That fine. The algorithms will automatically pick up new patterns in your data without a need for changing any configuration.