Data integration needs to be approached as an ongoing, iterative process whose goal is to improve and maintain the quality and availability of data throughout the enterprise.
The data integration life cycle has seven steps. There is an Informatica product to support you in each step.
- Access. All data is accessed, regardless of its source or structure. Data is extracted from arcane mainframe systems, as well as from relational databases, applications, XML, messages, and even documents such as spreadsheets.
Informatica PowerExchange
Informatica B2B Data Exchange
- Discover. Data sources—particularly poorly documented or unknown sources—are profiled to understand their content and structure. Patterns and rules implicit in the data are inferred, and potential data quality issues are flagged.
Informatica Data Explorer
- Cleanse. Data is cleansed to ensure that the quality of data is high in terms of its completeness, conformity, consistency, duplicates, integrity, and accuracy. Identities are matched, linked, and resolved, regardless of language, structure, or format. Data standards are enforced.
Informatica Data Quality
Informatica Identity Resolution
- Integrate. To maintain a consistent view of data across all systems, data is integrated and transformed to reconcile discrepancies in the way different systems define and structure various data elements.
For example, the marketing and finance systems may have completely different business definitions and data formats for “customer profitability,” and these differences must be resolved.
Informatica PowerCenter
- Deliver. The right data is delivered in the right format, at the right time, to all the applications and users that need it. Delivering data can range from a single data element or record to support a real-time business operation to millions of records for trend analysis and enterprise reporting. Data must be both highly available and secure in its delivery.
Informatica PowerCenter
Informatica B2B Data Exchange
- Develop and Manage. Data stewards, business analysts, architects, and developers need a powerful set of tools, including a common data repository and shared metadata, to help them collaborate on the development and management of data integration rules and processes.
Informatica PowerCenter
- Audit, Monitor, and Report. Data is monitored, and reports on the data are prepared. Key metrics, such as data quality, are constantly measured with an eye toward steady improvement over time.
This step’s goal is to track progress on key data attributes and flag any new issues for resolution and continual improvement once data is fed back into the data integration life cycle. This step includes maintaining a robust audit trail to maintain visibility into and control of data, as well as to reduce the costs of future change.
Informatica Data Explorer