Data management is the process of gathering, organising, securing, and storing data from organisation for analysis in making business decisions. Digital transformation has greatly shaken the once stable world of data management. Due to the IT-OT convergence, the amount of data is increasing and becoming more complex. As a results, organisations need to adopt a more effective data management architecture as a solution. The adopted data management architecture should give visibility, flexibility, reliability and security wherein this is achievable through data fabric. What are the key capabilities of data fabric that make it an effective data management architecture?
1. Data catalog
Data catalog acts as inventory data assets and combines metadata and data management, governance, and search capabilities to organise and evaluates data. This enables data to be easily searched and shared across all environments.
2. Data engineering
Data engineering is a practice related to designing and creating system that collect, store, and analyse data at scale. With data engineering being a key component in data fabric, organisations are able to build data pipeline that is reliable for operational and analytical use
3. Data governance
Data governance refers to the set of practices that underline the processes, metrics, policies and standards to ensure data integrity and security. With data governance, compliancy can be assured and made available with quality.
4. Data preparation and orchestration
Through data preparation, raw data (from external and internal resources) is transformed accordingly through various components which include pre-processing, cleansing and validation . Data orchestration, on the other hand, involves automated process that integrates, cleanses, and arranges data from various sources and then directed to the downstream service. Both data preparation and orchestration helps in providing enriched data that is useful and versatile for process and analysis.
5. Data integration
Data integration is a process that allows organisation combine data from different sources through various method and business process, for example ETL, data virtualisation, data replication and APIs.
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