Technovisions "Thriving on Data" mapped
This is the fifth blog in a series about Capgemini's Technovison and the mapping onto CORA. In the first blog Technovision was explained, being in short the provisioning of a clear picture of the information technologies that are the most relevant to the organizations' business drivers and how these technologies and their evolution will impact business.
With Technovision the business drivers are mapped to innovations as an input to the IT-Strategy. With the CORA model the gap between the IT strategy and actual implementation of software is bridged because the CORA model can be used at different levels (Enterprise level, project implementation level) and has the possibility to design and implement elements with a mixture of ‘architecture styles’ on the best fitted platform available (or planned).
By mapping the 17 identified key information technology trends within Technovision onto the layers and logical elements of the CORA model the impact on the IT landscape is visualized and assessed in more detail. In the second, third and fourth blog the key information technology trends within the "You Experience", "We Collaborate" and "Process-on-the-Fly Collaborate"cluster were mapped and assessed. In this blog post this is described regarding the "Thriving on Data"cluster.
The "Thriving on Data" cluster describes how to connect the use of data to strategic business objectives by constantly reading, analyzing and reacting to information inside and far outside the company boundaries. Information thus is becoming a corporate asset, which serves all strategic and operational parts of the business. Thanks to emerging open standards and Service-Oriented Architecture, intelligence now truly becomes a real-time, integrated part of whatever system or device we are using. It supports real-life decisions on the spot wherever and whenever they are needed but it also provides the deep insight to continually improve business performance and be prepared for the future. Also, opening up data to the organization and to the outside world provides new opportunities to
demonstrate transparency, invite collaboration and tap into an unexplored world of creativity and innovation.
- Real-Time Intelligence: real-time, integrated Business Intelligence that support decisions on strategic, tactical and operational levels.
- Advanced Analytics: statistical analysis in order to discover and understand historical patterns with an eye to predicting and improving business performance in the future.
- Open Data: making business data freely available without restrictions from copyrights, patents or other mechanisms of control.
- Mastered Data Management: mastering and governing the core data of an organization.
As shown in the figure the capabilities have a clear focus on the Application and Data Composition Layer. The other horizontal layers are layers supporting this layer depending on the architectural style used. For the sake of simplicity the capabilities are described separately, but combinations of capabilities are possible, for instance using Open Data in combination with Mastered Data Management.
Providing intelligence is about injecting structured and unstructured information (i.e. Enterprise Content Management) in the actual, day-today flow of work and the applications that are being used. Open standards and SOA are the catalysts of this evolution. For this reason the relationship with SOA Governance is mapped explicitly onto the model.
Many acquisitions have taken place in the market of business information management, leaving the big technology suppliers (SAP, Oracle, IBM, Microsoft and EMC2) as leaders. However, specialized suppliers still have strong positions as well. In some sectors, the interest in open-source-based intelligence platforms is increasing. And on the wave of the cloud phenomenon, the first generation of “BI-as-a-Service” suppliers is entering the market. Because many solutions/platforms are built based on the N-tier architecture style or a combination of N-tier and SOA architecture style special care must be taken when assessing them.
Advanced Analytics is about true business insight, supported by advanced analytics tools. Common applications of analytics include the study of business data using statistical analysis/data mining in order to discover and understand historical patterns with an eye to predicting and improving business performance in the future. Where real-time intelligence may be embedded in the activities of every employee of the organization, advanced analytics usually provide more specialized tools for the corporate strategy and decision makers.
Advanced Analytics solutions/platforms are primarily built based on the N-tier architecture style with a focus on powerful, extensive computation.
Open Data is about leveraging the innovative and creative powers of the community on one hand and increasing corporate transparency on the other hand. The data can be provided exclusively to the internal organization, but more often it will be available to any interested party in the outside world. This will often be actively stimulated and supported by the organization that donates the data (and it may even involve showcases, competitions, etc.). Ubiquitous open standards obviously push this trend forward and, indeed, much open data is published in XML-based formats and/or services.
Constantly improving search technology will also help organizations to fully exploit all available data. The search will be able to include unstructured information but also structured information contained in databases, transaction systems, document management systems, knowledge bases, Intranets, etc. Open Data is often delivered using the SOA and ROA architecture style or a combination of the two. For this reason the relationship with SOA Governance is mapped explicitly onto the model.
Mastered Data Management
Mastered Data Management is needed inside an organization, and data synchronization concepts are required for accurate publication of that data across an ecosystem of partners. Truly mastered data management involves, besides applying a new generation of tools, a data governance component. Data governance pertains to having clear data owners and users, having clear business policies regarding what is good master data and what is not. It is also about providing constant reports and alerts to master data owners and promoting proper stewardship of healthy master data across the organization. For this reason the relationship with Security and IT Governance elements is mapped explicitly onto the model. Because MDM solutions can be implemented using both the N-tier and the SOA architecture style special care must be taken when designing the MDM-processes to avoid mixing them in a wrong way.
In the next blog post the technology cluster "Sector-as-a-Service" will be mapped onto CORA.
- Assessing IT solutions with CORA
- CORA and Archimate
- Architecture Styles and CORA
- ERP and PaaS
- CORA and Application Lifecycles
- CORA Methodology (Project level)
- The roadmap for Fusion Applications, CORA is there to help
- Technovisions "Sector-as-a-Service" mapped
- Business Logic and the CORA Model, Part II
- CORA and Cloud Computing: Static versus Dynamic View
- Technovisions "Thriving on Data" mapped
- CORA Foundation
- Business Logic and the CORA Model, Part I
- CORA and IBM
- CORA and Microsoft
- CORA and Cloud Computing: Overview
- Technovisions "Process-on-the-Fly" mapped onto CORA
- Risk aware design: using CORA to investigate an IT solution
- A ROA based iPhone App for SAP: Part II
- A ROA based iPhone App for SAP: Part I
- Technovisions "We Collaborate" mapped onto CORA
- SAP platform decomposition with CORA: SOA/ROA style
- 'Why' Driven Solution crafting
- CORA and TOGAF
- SAP platform decomposition with CORA: N-tier style
- Requirements for CORA
- CORA and Oracle
- Technovisions "You Experience" mapped onto CORA
- CORA and SAP
- CORA in action: design guidelines to implement repositories
- The basis of all, your data
- CORA and IAF
- Technovision and CORA - Overview
- The importance of an Integration layer