In Part 1 of the series, we discussed some of the unique traits of enterprises that adopt the ‘platform mindset.’ In this blog, we will further highlight how the next generation of value creation is being driven through analytics.
3. Multi-layered Technology Talent Structure
Companies with a “platform mindset” manage to get their organizational set-up and agile delivery model, right. They tend to create a well-integrated and coordinated three-layered analytics technology team structure with clearly delineated decision rights, roles and responsibilities between them.
The three layers are:
- Business Technology team: – These teams are embedded within the business units. They tend to possess domain, data and analysis skills relevant to a specific business function.
- Platform Engineering team: – This team is responsible for developing the common software components library. They closely collaborate and coordinate activities with the solution teams within the business units and IT team to define and execute on their component library development roadmap.
- IT team: – This is the company’s central information technology team which has control over the company infrastructure, back office systems, applications, network, security and data.
4. A Next-Generation Platform that is used to deliver analytical products and solutions
Companies with a “platform mindset” focus on the development of their next generation platform with modern, scalable, open source distributed technologies like Apache Hadoop, Apache Spark, Apache Kafka and in-memory databases as a foundation to deliver analytics across multiple domains to both internal and external stakeholders. The platform must also be developed as a modular, micro-services based components architecture. The importance of modularity and component-based architecture are the bedrock of scalability and robustness for these platforms.
5. Common software components library
Development of a library of common software components that can be assembled on-demand, shared and re-used across the enterprise is critical for the next-generation platform. The platform governance team must centralize this platform engineering function to ensure that there is consistency and standardization of technology components and no duplication of efforts among various technology teams.
The common software components must:
- enable the various data and analytics capabilities identified by the various business teams within the enterprise and external stakeholders
- be meta-data driven and flexible enough to take a standardized set of input parameters and deliver standardized outputs from different analytics solution groups.
- facilitate seamless integration with external vendor components, leverage open source technologies as much as possible and avoid vendor lock-in and high total cost of ownership.
PwC is leading the charge with emerging technology industry leaders like Cloudera to adopt a platform mindset to move from a vertical, siloed approach that limits data’s value to an integrated, horizontal, platform centric mindset that maximizes data’s potential and unlock values for clients. Our analytical assets and applications are built on these robust and scalable data platform principles. To learn more, please visit our analytics apps marketplace at https://marketplace.pwc.com/ and look through our multi-domain, multi-industry solutions which will help unlock business value out of your enterprise data assets. You can also explore PwC’s Customer Insights Platform on the Cloudera Solutions Gallery.