What is Data Quality¶
The key concepts, native features and customer use cases Timextender provides for maintaining reliable, accurate, high-quality data across your entire business landscape. This is a great way to kick-start your learning.
Timextender Data Quality is a platform designed to support successful data governance. It provides a flexible, lightweight approach to managing data quality by connecting to source data or business solutions. You configure controls that address real business problems and continuously monitor data over time. That builds trust in data, improves the accuracy of BI, reports and decision-making, and prevents bad data from entering systems.
When an exception to a configured control is detected, the system automatically generates an exception, assigns it to the responsible individuals, and sends timely notifications — so responses to data challenges are fast and effective.
Data governance means implementing policies, processes and controls that ensure data quality, integrity and security. It helps organizations manage data effectively, comply with regulations and improve decision-making. Timextender's data governance features help maintain trust in data, drive efficiency and unlock the full potential of information assets. The module connects to source systems, databases, data warehouses and APIs, configuring controls for meticulous data analysis.
Core features¶
| Feature | What it gives you |
|---|---|
| Effortless data quality control | Implement new data quality controls quickly through an adaptable rule designer, promoting collaboration between IT and business teams. |
| Data issue overview | A comprehensive overview of data quality issues in a single, transparent platform, enhancing visibility and informed decision-making. |
| Responsibility delegation | Delegate responsibilities easily, create new rules, and dig into details with revision logs. |
| Continuous monitoring and analysis | Continuous monitoring and analysis of data identifies and addresses discrepancies promptly, leading to streamlined and efficient business operations. |
| Business process monitoring | Track the status of data quality issues and generate reports on data KPIs, showing the impact of your data quality initiatives. |
Who uses Data Quality?¶
Thousands of companies in nearly 100 countries around the world use Timextender. Every industry vertical needs data, so any industry vertical can use Timextender.
Vodafone Iceland · Air Atlanta · JYSK · Marel — and many, many more.
Use cases¶
| Use case | What it means |
|---|---|
| Proactive data quality improvement | Validate and improve data quality proactively, ensuring consistent data integrity. |
| Real-time issue remediation | Quickly restore data quality when problems emerge, minimizing disruption to business operations. |
| Flexible integration | Connect to any data source and integrate with your ticketing system of choice. |
| Customizable quality controls | Build data quality controls tailored to your business rules. |
| Enhanced BI accuracy | Improve the accuracy of BI, reports and business decision-making with reliable data. |
| Powerful data stewardship | Robust data stewardship capabilities, ensuring responsible data management. |
| Efficient exception handling | Assign exceptions directly to data owners for fast, accurate resolution. |
| Increased trust and transparency | Gain insight into data health with improved trust and transparency. |
| Dynamic dashboards | Flexible dashboards, with connections to Power BI, Tableau and more, to give visibility into data quality and trends. |
Data quality controls¶
There are three data quality controls.
Query¶
A query, which defines a business rule, into a single source of data. For example:
- Missing or invalid attributes
- Duplicate entries
- Outdated entries
Compare query¶
A query into two source systems that should have comparable data. For example:
- Products existing and having the same entries in two systems (ERP + CRM)
- Orders matching between ERP and manufacturing
Data changes¶
Important data that needs multiple pairs of eyes to verify when changed. For example:
- Item creation in Product, Vendor and Customer
- Price list changes
- Vendor bank transfer information
Quiz¶
Two questions to check yourself on:
- What are the 3 data quality controls?
- What are 3 common use cases?
Related reference¶
- Data Providers — connect Data Quality to your source systems.
- Query Control — build your first quality check.
- Data Cleansing — the Data Integration side of data quality.
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