Squadra - Data Quality

Approach

Create A Data Quality Improvement Plan In 5 Steps.

High-quality data is key in today’s business environment. But as businesses grow, maintaining this standard gets harder. How can you ensure consistent data quality at scale?

Preparation

A data quality assessment starts by identifying the stakeholders, alignment on scope and data domains to be assessed, so you understand the available data and tools and can agree on timelines.

Discovery

Next, we conduct the interviews to understand the current and future state in terms of data processes, -organisation, -architecture and -structures, system landscape and data quality tooling. The interviews also provide insight in business goals, key bottlenecks and their business impact.

Data quality assessment

Once we have access to the data, it can be profiled against defined KPI’s and quality targets, which enables quality analysis in terms of data completeness, correctness and consistency.

Data quality gap analysis

The results of the discovery and data quality assessment are consolidated, which allows us to compare the current state with business goals. This results in a data quality gap and related impact analysis.

Data quality improvement plan

A detailed data quality improvement plan can now be created, which includes priorities, phasing, required resources, investments, dependencies and proposed process and/or organizational mitigations.

Services

Get Insight In Your Data Quality And Processes.

Data quality management enables organizations to continiously measure and improve the quality of their data. This ensures accuracy and reliability as your business evolves and transforms data into a strategic asset for your organization.

Data quality assessment

Our data quality assessment framework measures your data capabilities and offers an actionable improvement project and roadmap.

Data quality dashboarding

After implementing PIM or MDM systems, the lack of data quality becomes even more visible and often remains a challenge. We can help you make data quality management measurable by enabling step-by-step improvements for sustained success.

AI-based data quality improvement

Our PowerSuite SaaS-solutions help you enrich your product data and improve data quality beyond the possibilities of most PIM systems, using the power of AI.

Learn more

Data remediation

Improve your data step-by-step using Squadra’s expertise and capabilities, that vary from DQ assessments to data structure improvements and DQ dashboarding up to AI-based enrichment and low-cost manual validation and/or enrichment.

Benefits

Trustworthy Data Drives Efficiency And Business Growth.

Better Analytics and Decision-Making

Accurate and consistent data improves the accuracy of analytics and predictive models, leading to more reliable insights and forecasts to ensure informed and confident business decision making.

Increased Efficiency

High-quality data minimizes time spent on correcting errors and resolving inconsistencies, leading to optimization of processes, streamlined operations and cost savings.

Improved Customer Satisfaction

Clean and accurate data ensures personalized, timely and reliable interactions and transactions with customers, as well as improved targeting and enhancing customer experience and loyalty.

Regulatory Compliance and Risk Management

Trustworthy data ensures compliance with legal and industry regulations and reducing the risk of fines, penalties or legal issues.

Business Growth and Scalablity

High-quality data supports cross and upsell, improved targeting and future expansion, by enabling seamless integration with new systems, technologies and processes.

Better Analytics and Decision-Making

Accurate and consistent data improves the accuracy of analytics and predictive models, leading to more reliable insights and forecasts to ensure informed and confident business decision making.

Increased Efficiency

High-quality data minimizes time spent on correcting errors and resolving inconsistencies, leading to optimization of processes, streamlined operations and cost savings.

Improved Customer Satisfaction

Clean and accurate data ensures personalized, timely and reliable interactions and transactions with customers, as well as improved targeting and enhancing customer experience and loyalty.

Regulatory Compliance and Risk Management

Trustworthy data ensures compliance with legal and industry regulations and reducing the risk of fines, penalties or legal issues.

Business Growth and Scalablity

High-quality data supports cross and upsell, improved targeting and future expansion, by enabling seamless integration with new systems, technologies and processes.

Assets

Our Data Quality Assets.

8 aspects of Data Quality

Data Quality is at the heart of PIM and MDM. When improving the data quality of your organization, we focus on 8 core aspects.

Data Quality metrics

Define a structure for creating insights in data quality during the data life cycle.

8 aspects of Data Quality

Data Quality is at the heart of PIM and MDM. When improving the data quality of your organization, we focus on 8 core aspects.

Data Quality metrics

Define a structure for creating insights in data quality during the data life cycle.

Insights

Transform Your Business With Data-Driven Insights.

Discover the latest insights about data quality and a solid data foundation.

ETIM Data Exchange 'On The Move'

5 Steps to Develop a Solid Business Case for MDM

What is MDM and Why Do You Need It?

Data Literacy

How DaaS Enables Real-time, High-volume Access to Current Master Data

More insights

ETIM Data Exchange 'On The Move'

5 Steps to Develop a Solid Business Case for MDM

What is MDM and Why Do You Need It?

Data Literacy

How DaaS Enables Real-time, High-volume Access to Current Master Data

More insights

Squadra supported Kramp in streamlining their master data management by introducing best practices for data standardization, system implementation and building an integrated MDM organization.

View client case

Jos Schreurs

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