Nthinsight | Data Quality and Governance

The importance of having accurate data and it's governance

Having accurate data free of anomalies, duplicates and errors gives the management tremendous confidence to rely on it, make meaningful interpreations and create data driven strategies. New technologies such as marketing automation and AI are also influenced by data quality. These tools have enormous potential in today’s business world, but success heavily depends on the value of data. The more useful data you provide, the algorithms can produce faster and better results.

Project Scope

Solutions

Exception Reporting and Governance Forums

Policies

Documented framework for Business KPIs

Alert and Remediation

Cross funtional collaboration and outcomes

Systems

Data warehouse, BI Tools, CRM software

Support and Maintaincence

Automated solutions

Project goals

Create a result oriented robust solution that monitors the data quality at ingestion to minimize anomalies and data errors. Once the data is ingested and made available for broader consumption, the framework will consistently keep track of data reliability, accuracy and completness. Regular checkpoints to ensure the data quality issues are fixed and not causing any disruptions in usage.

Optimize data management process
Starting at the top during data onboarding to keep essential checks on data quality KPIs aligned to business KPIs
Monitoring at data ingestion, data transformation and data visualization layer for faster root cause analysis
Alert and subscriptions for remediation
Continuous maintainence of the framework and iterate for new and existing data issues

Data quality is a fundamental attribute as data is powerful and has a stronger impact on various aspects of a business, including customer satisfaction, accuracy of decision making and compliance

Final outcome of the project

We know how significant it is to base your organization's decisions and plan future goals according to the data that is gathered. However, what determines the success of all these business decisions and goals is the quality of the gathered, stored, and consumed data. Hence it is of utmost importance to ensure the quality of data reports and assets is top notch to have complete confidence on decisions rendered via the underlying data.

Defining and documenting the gold standard of data quality that best fits your business strategy and vision
Report on the state of quality and the exceptions that exist within a data quality dashboard.
Automated and “on-demand” technology solutions should be implemented as well, so dashboard insights appears in real time.
Data Repairing and Remediation
Re-initiate the data processes if their functioning was at risk or compromised by the defected data.
Create data glossary and define governance standards to minimize data quality issues.

A solid data governance program is the foundation for enterprise-scale data quality, providing a framework that aligns people, processes, and technology. Quality data is complete, verified, and validated – and it also underpins any data integrity plan.