Databoss

Databoss: Data Quality for the Data Age

Automatically detect and explain issues in your enterprise data. Databoss reduces overall data downtime and helps create trust in your data.

Be the first to know and to resolve data problems.

Detect sophisticated and complicated errors that slip through simple hard-coded rules and checks.

Importance of Data Quality

Data quality has always been important but in the age of data-driven everything it might be impossible to compete with bad data.

Data Uptime

Data issues are costly to resolve. The longer it takes to identify the problem, the costlier it gets to resolve it. Minimize reaction time and costs and create transparency.

Data Trust

If you cannot rely on your data 100% all of the time, you cannot rely on it at all. Hoping that most data should be right most of the time is not acceptable.

Good Decisions

In the worst case scenario, you don’t even notice the data quality problems. This will lead to bad decisions which will erode trust in your data and it will lead to bad business outcomes.

Poor data quality costs organizations an average $12.9 million per year.

How AI increases Data Quality

Detect sophisticated and complicated errors that otherwise would go unnoticed with simple hard-coded rules and checks.

Databoss allows you to deploy intelligent quality checks at scale – ensuring that every data packet conforms to the highest quality standards.

Check complex patterns and correlations: verify that your data’s internal complex structures come as expected
AutoML: automate sophisticated Machine Learning tasks and let Databoss define the most meaningful tests for you

Learning over time: Databoss tracks changes in your data sets over time and correctly anticipates them when inspecting new data
Alerts: get immediately notified when your data shows anomalies and prevent data downtime

Databoss Workflow

Set up data checks: Define what data sets should be validated and identify the most critical steps in your data flows.
Monitor data quality: Let Databoss automatically analyze and test data flows with its built-in AI and Machine Learning methods.

Manage exceptions: Get notified immediately if new data deviates from expected health levels. Minimize time from detection to reaction in order to minimize data downtime.
Learn, update and improve: Feed back systemic external changes to Databoss so that checks can be adjusted to new levels of “normal”.

Data Quality for All Industries

Companies across all industries are faced with challenges regarding their data sets.

Data Quality Stakeholders

Databoss for everyone

Data Engineering

Easily integrate into any data stack and connect to all services with extensive APIs. Optimize data engineering productivity.

Data Analyst

Discover data issues before your users do. Add smart checks with AI to your data flows and data sets in minutes. Align data pipelines with business objectives.

Data Science

Use smart checks to ensure data reliability and quality across algorithms, models and source.

Business User

Increase team velocity, Improve stakeholder trust, Minimize business risk.

FAQs

Is it a platform? What about my existing EAI infrastructure?

No, Databoss is not a platform for data pipelines across the enterprise. It is designed to complement your existing infrastructure and add new capabilities to help improve data quality. Databoss allows you to define and manage intelligent data checks that are deployed to your existing data pipelines.

Do I need to scrap my existing quality checks?

Most companies have simple data checks in place. Databoss can also perform those checks but its true value lies in detecting and preventing complicated and sophisticated data failures that otherwise are expensive and take a long time to detect and fix.

Do I need Data Science skills and resources to implement Databoss?

You don’t have to have any advanced Data Science skills. Databoss is a no-code solution and automates all Data Science tasks for you. What you should have: a basic understanding of the types of algorithms and what they do in order to be able to understand the results that Databoss gives you.

Does Databoss support transformations? Why not?

Databoss is designed to be added to your existing EAI and data pipeline infrastructure in a minimally-invasive way. Its core focus is to analyze and compare data sets to alert users when results indicate a data failure. Transformation and data wrangling are different tasks that should be implemented via other tools.

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