Data Integration Suite solutions

Data Integration Suite components provide the tools to address various data integration challenges in your enterprise.

Table 1-2 provides a list of common data integration problems including problem details and the solution from DI Suite.

**Table 1-2: Common data integration problems and solutions**
Problem	Details	Solution
Trapped, displaced, disconnected, and inaccessible data	Valuable data is trapped in diverse data stores or incompatible data schemas, and blocked by legacy systems. Data among data stores is not integrated. No real-time data is available as changes in data transactions between data stores are not distributed and synchronized.	Replication component – connects to any supported heterogeneous data store and keeps the data in your enterprise integrated and near real-time.
No single view of enterprise data	Access to operational data impacts the operating performance of the system. Warehoused data is not real-time. No unified view of operational data from various data stores. This affects access to critical data for time-sensitive applications.	Data Federation component – helps you to: Achieve single view across enterprise data. View operational data in real time. Create distinct views to view operational data and warehouse data.
No way to provide a unified view of enterprise data without giving complete user access to this data	Distinct tools are used to view different data across the enterprise. Access restrictions and stringent sharing rules restrict users from accessing certain data.	Data Federation component – allows you to copy and share data across the enterprise that has strict data share and copy rules. You can also enable single or distinct views of your enterprise data.
No automated way to use real-time and historical data to improve the efficiency and quality of business processes	Business Intelligence (BI) tools access only the data warehouse and not operational data stores	Data Federation component – helps you to federate between data in data warehouse and operational systems to obtain a combined view of current and historical data.
No way to identify and prevent unauthorized use of services	Developers write services and embed the access logic within their code. Unable to add permissions in the code.	Data Federation component – provides the ability to create users and set access permissions for each service. This enables you to separate the business logic embedded within the code from the service access.
No single solution to deal with large volumes of unstructured information in the enterprise	Manual tagging of documents based on the content is done to include these documents for search. This is extremely labor intensive and requires extensive tagging of documents. Use of search engines to perform a keyword search instead of context-based search to search similar content. Keyword search displays results that match in keyword but in a different context.	Search component – enables you to search unstructured data, as well as data in the relational databases. This component provides the ability to do automatic categorization of your documents based on its content and enables search of documents containing similar text, in natural language.
No holistic view of the enterprise after acquisitions	Each acquired business generates its own reports. Consolidating reports is difficult and time-consuming	DI Suite provides the following choices: Replication component – replicate all data to a central database and create aggregated views. Data Federation component – federate access to data in various businesses.
Information across the enterprise is not synchronized or real-time and this impacts users who use applications to access data	Applications cannot obtain events as they occur in data stores. Central repository is updated with data changes only at intervals. Therefore, data is not current.	Real-Time Events component – changes from the source database are captured and pushed as events in a message bus. Applications that subscribe to these events apply the changes to the target database.
Difficult to manage complex data extraction methods and data transformation rules	Various legacy systems require distinct data extraction methods. Building and managing different data extraction methods is difficult and cumbersome. Target data warehouse has complex transformation rules that increase the complexity of data load.	Sybase ETL component – provides GUI tools you can use to build and manage multiple data transformation and loads from multiple legacy systems to your target data warehouse. It helps you: Monitor transformation flows in a comprehensive simulation and debugging environment. Maintain data quality and enhance speed of development of transformation flows through intuitive reuse of previously built transformation processes. Execute transformation flows in a scalable, grid architecture available on a variety of platforms.