building up a complete picture of a person, company or any entity is a challenging task. With different databases, systems and applications containing pieces of information about entities, making sense of those pieces and linking them together is a real headache. For example, how can we identify a single customer across multiple channels or platforms and provide a unified experience? Or, how can we verify the identity of an employee, contractor or partner across different workflows and systems to enforce access control policies? The answer lies in centralizing identity and master data.
What is identity?
Identity refers to the unique set of attributes or characteristics that describe a person, organization, device or any other entity. These attributes can include personal information (such as name, mailing address, email address, phone number, social security number), biometrics (such as fingerprint, facial recognition, voice recognition), behavioral patterns (such as browsing history, purchase history, social media activity), credentials (such as username, password, security token) and more.
Why centralize identity?
Centralizing identity means that all the identity data related to an entity is stored in a single location or repository, accessible by multiple systems and applications. By doing so, we can achieve the following benefits:
- Consistency: Every application that uses identity data will be referring to the same source of truth, avoiding discrepancies and errors.
- Efficiency: Updating and managing identity data in a central location is quicker and easier than doing so in multiple systems.
- Reusability: Once identity data has been centralized, it can be reused across different workflows and systems, reducing redundancy and improving data quality.
- Security: By enforcing access controls and auditing mechanisms on the central repository, we can secure the identity data and mitigate the risk of data breaches and fraud.
How to centralize identity?
Centralizing identity means creating and managing a single, authoritative source of truth for all the identity data related to an entity. This can be done by implementing a master data management (MDM) solution that serves as the central repository for identity. An MDM solution provides the following functionalities:
- Data integration: bringing together identity data from different sources and consolidating them into a single view of the entity.
- Data quality: cleansing, standardizing and enriching identity data to ensure accuracy and consistency.
- Data governance: defining business rules and policies for identity data management, enforcing compliance and regulatory requirements.
- Data access: providing secure and controlled access to identity data for different systems and applications.
How to master data for better record linkage?
Master data refers to the set of homogeneous and structured data that describes the most important entities (such as customers, products, employees, etc.) of an organization. Master data includes key attributes such as name, address, date of birth, account number, etc., that serve as the primary identifiers for those entities. Master data is critical for record linkage because it enables the matching and linking of different instances of the same entity across different sources.
Why master data?
Master data serves as the core reference data for an organization. By maintaining accurate and consistent master data, we can achieve the following benefits:
- Efficiency: avoiding the duplication of effort and resources by reusing the same master data across different systems and processes.
- Agility: responding quickly to changes in the business environment by updating the master data and propagating those changes to all the systems that use it.
- Accuracy: ensuring that the master data is correct and consistent across all systems, avoiding errors and misunderstandings.
- Compliance: enforcing business rules and regulatory requirements by controlling the changes and access to master data.
How to master data?
Mastering data means creating and managing the unique identifiers and attributes that describe the entities of an organization. This involves the following steps:
- Identification: identifying the key attributes that uniquely identify an entity and that are relevant to the business processes and applications.
- Standardization: standardizing the values of those key attributes across different sources and systems to ensure consistency and accuracy.
- Matching: using sophisticated algorithms and rules to match and link different instances of the same entity across different sources, based on the key attributes.
- Merging: consolidating the matched entities into a single, golden record that serves as the master data for that entity.
- Governance: defining and enforcing the business rules and policies for master data management, ensuring compliance and data quality.
Centralizing identity and mastering data are two important steps towards achieving better record linkage and data quality. By creating and managing a single, authoritative source of truth for identity and master data, we can provide consistent, efficient and secure access to those data for multiple systems and applications. This in turn, enables us to improve the customer experience, enhance the employee productivity and reduce the risk of data breaches and fraud. To get started with centralizing identity and mastering data, you can explore various MDM solutions available on the market, such as Informatica MDM, Talend MDM, or IBM MDM. Join us at entityresolution.dev for more insights and best practices on entity resolution, master data management, centralizing identity, record linkage, data mastering and much more!
Editor Recommended SitesAI and Tech News
Best Online AI Courses
Classic Writing Analysis
Tears of the Kingdom Roleplay
JavaFX App: JavaFX for mobile Development
LLM training course: Find the best guides, tutorials and courses on LLM fine tuning for the cloud, on-prem
GCP Anthos Resources - Anthos Course Deep Dive & Anthos Video tutorial masterclass: Tutorials and Videos about Google Cloud Platform Anthos. GCP Anthos training & Learn Gcloud Anthos
Learn Python: Learn the python programming language, course by an Ex-Google engineer
Learn Beam: Learn data streaming with apache beam and dataflow on GCP and AWS cloud