Purpose-driven, trusted insights from big data lakes born in the cloud

Organizations are experiencing unprecedented disruption in the marketplace. Data has transitioned from a back-office topic to a board-room discussion point. Because more data is available about customers, competitors, and internal operations, organizations have enormous potential to harness the power of the data to drive faster and more-trusted business insights. Data is now the lifeblood of automated decision arteries in organizations developing a new generation of services powered by AI and digital labor.

Digital transformation is not simply a matter of adopting new technologies like Apache Spark or spinning up new environments in the cloud. In fact, so-called “quick-hit” projects started in the name of agility have left organizations with significant technical debt and maintenance nightmares. Agility and flexibility are undoubtedly necessary for execution, but without a well-architected enterprise data management strategy in place, the returns on agility can be modest, if not negative, as organizations struggle to deal with fragmented data, fragmented processes, and a fragmented understanding of the truth.

“This is the moment to reimagine your business. This is the moment to put AI and cloud to work for you.” —Steve Jones

Embrace cloud now

Whether or not your organization has a cloud mandate, the trend toward cloud and hybrid execution engines is inevitable. You must design data and business processes that can be reused and repurposed through these market and technology transitions. A comprehensive end-to-end approach to data management for enterprise data lakes that fully abstracts and supports multiple runtimes including SQL, Spark, Java, Scala, Graph, Apache on Amazon Web Services, and Microsoft Azure, etc. shields your organization from the rework nightmares and maintenance of underlying technology changes. Automated deployment and scaling provided by serverless management eliminates unnecessary administrative labor while helping optimize for cost, performance, workload isolation, unitized billing and other modern considerations. By connecting to a diverse category of data and processing it in any environment on premises or in the cloud, an end-to-end approach to data management for enterprise data lakes enables you to be ready for digital, disruption and change.

Shift Happens” – Keith Reid

Embrace the agility and flexibility of technology diversity, while mitigating risk

New innovations over the last 5-10 years have fundamentally changed the data landscape for organizations and presented diverse benefits of different technologies available on the market. But no single technology solves every problem. In addition, new specialized technologies often carry the cost and burden of new development teams and development process for specialized technologies. The opportunity to harness data fully can only come by embracing a single, common, abstraction layer – an integrated data management solution that can seamlessly execute across multiple technologies. Moreover, a comprehensive end-to-end approach to data management eliminates much of the risk in adopting new innovations. Embracing the Speed, Scale, and Flexibility of Digital Democratization of Data is no longer purely in the domain of IT. The days of tightly controlled databases and data warehouses are simply over. Business analysts are increasingly self-serving data.

Some IT leaders call it shadow IT, but access to data, is paramount to business with or without IT enablement. Ungoverned self-service access to data that should be secure and auditable can place organizations at risk for maintaining compliance in an increasingly complex global regulatory climate. Newer artificial intelligence based data catalog and data preparation technologies act as smart coordinators for data consumers by providing the right data to the right people at the right time while maintaining access and audit security. With the right framework, architecture, tools, governance and approach the path to automation and artificial intelligence can be less fraught and less contentious.

“There is no digital or AI without good, clean, complete data.” —Scott Sweet

“Together we do projects no one has done before.” —Dusty Jackson

The days of multiple Enterprise Data Warehouses, each promising to be the sum of all enterprise knowledge, are over. The modern data architecture from Capgemini and Informatica forms a center of gravity of data with purpose driven distillations. We have developed a Globally Federated Data Lake Template that is fully customizable and GDPR certified. This template is ready to use and entirely supported on Amazon Web Services and Microsoft Azure. Multi-level security, Master Data Management, Data Quality, a comprehensive Data Catalog and self-service data preparation tools are part of the foundation. Over 20 projects have successfully deployed on this template. Capgemini and Informatica engineering teams are in lock step, ready to support any product evolution that is required. Ephemeral computing and server-less architecture is at the heart of our projects, allowing our customers to scale easily and pay per use. Our emphasis on delivering value through AI and cognitive capabilities put us ahead of the game.

Why work with Capgemini and Informatica?

Capgemini is a market leader in delivering data management strategy and implementations across the data landscape. With over 5,000+ trained Informatica professionals, clients have worked with Capgemini to not only evolve their legacy information architectures in order to exploit massive data volumes and new data types, but also to embark on new and innovative projects exploiting the latest evolution of technology. Informatica is the only Enterprise Cloud Data Management leader that accelerates data-driven digital transformation. Informatica enables companies to fuel innovation, become more agile, and realize new growth opportunities, resulting in intelligent market disruptions. Informatica powers modern applications and analytics for IT and business users through cloud, on-premises, and big-data solutions