Data Quality Services
WE ARE SPECIALISTS IN DATA QUALITY MONITORING
We will put you in full control of your data so you can quickly detect and address quality issues before they impact your business.
Data Quality Services
WE ARE SPECIALISTS IN DATA QUALITY MONITORING
We will put you in full control of your data so you can quickly detect and address quality issues before they impact your business.
The importance of data quality has never been greater
Data become ubiquitous and companies rely on it to create insights, optimize processes, and improve decision-making. The latest data industry shift into storing data in the data lakes or building a data mesh architecture has given data teams greater flexibility when it comes to managing their data assets. But this results in more data sources and increasingly complex data pipelines.
Delivering trusted data in this new context requires continuous data quality monitoring. Only then you can truly detect the data quality issues before they impact your business. Check our data quality services.
OUR DATA QUALITY SERVICES
We bring the practices, frameworks, and experience to ensure high-quality, trusted data. We are ready to jump in at any point of your data quality journey.
We created DQO, an open-source data monitoring platform that easily integrates with CI/CD pipelines, and supports code completion and multidimensional data quality tracking.
- We develop data quality strategies tailored to the organization's needs
- We design custom data quality checks that detect issues from a business perspective
- We build custom data quality dashboards that track data quality KPIs
- We monitor petabyte-scale tables on a daily basis
We detect data quality issues in the most popular databases
Our DATA QUALITY experience in numbers
3
clouds
(GCP, Azure, AWS)
10+
real-world sources used for cross-check validation
40+
suppliers monitored for data sharing KPIs
800+
custom data quality checks defined
1000+
tables observed daily
5000+
custom rules evaluated daily
Our DATA QUALITY experience in numbers
3
clouds
(GCP, Azure, AWS)
10+
real-world sources used for cross-check validation
40+
suppliers monitored for data sharing KPIs
800+
custom data quality checks defined
1000+
tables observed daily
5000+
custom rules evaluated daily
Our clients were featured in
When you should consider
a data quality initiative?
Data Migration
Your data warehouse is migrated to the cloud or a different platform. To ensure a successful migration you should also validate data integrity between the source and target system. This is also the right time to start taking care of your data quality.
Data Lake
You have a lot of unverified data coming into your data lake. Data is not loaded on time, and the data format in new files is wrong. Data quality rules for all data sources should be defined and tracked for all tables.
Data Mesh
You share data across data lakes and between teams. This is the right time to define and track data quality KPIs that are always met. No more invalid or missing data.
Data Sharing
You share data with your customers who require high-quality and timely data. Or perhaps you are a customer who receives data shared by your suppliers, marketing agencies, or related business entities. This is the right time to track data quality KPIs for timeliness, completeness and validity.
Industry-specific data quality challenges
Finance
Compare the data between relevant systems. Always make sure that the numbers you see on the dashboards are valid and match the ERP system.
Healthcare
Ensure regulatory compliance with the data stored in your data warehouses. Make sure that no data is missing or in the wrong format. Verify the format of HL7 messages.
Marketing
Track campaign performance and budgets with confidence that all the campaign data loaded into your data warehouse is up-to-date, complete and accurate.
What kind of problems do we measure?
Data quality dimension
Metric
Timeliness
Completeness
Has the data changed over time? Has the data not been corrupted?
Is the data complete? Has the data not been lost?
Validity
Consistency
Does the data change smoothly?
Are there any anomalies occurring?
Uniqueness
What is the percentage of unique data?
Other services we provide
Data Engineering
We can build data warehouses, data lakes, and data pipelines. We have experience in Big Data projects.
Business Intelligence
We can design dashboards and create data marts. Engage us for Google Data Studio or Power BI projects.
Custom Software
We can build custom software in the most popular tech stacks: Java, Python, .NET, React.js, and Vue.js.
Machine Learning
We specialize in anomaly detection and time series analysis.
LET’S TALK ABOUT YOUR NEXT PROJECT
Tell us about your data platform and problems and we will contact you as soon as possible.
