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For Enterprise Architecture Professionals
Forrester's Overview Of 22 IoT Data Management Solution Providers
June 6, 2019Noel Yuhanna,
Michele Goetz
You can use internet-of-things (IoT) data management solutions to deliver a comprehensive view of IoT data, become significantly more productive, and accelerate IoT initiatives. But to realize these benefits, you'll first have to select from a diverse set of vendors that vary by size, functionality, geography, and vertical market focus. Enterprise architecture (EA) professionals should use this report to understand the value they can expect from IoT data management solution providers and select vendors based on size and functionality.
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For Enterprise Architecture Professionals
The 12 Providers That Matter Most And How They Stack Up
June 4, 2019Noel Yuhanna
Database-as-a-service (DBaaS) has become critical for all businesses to build and support modern business applications and operational systems. In our 27-criterion evaluation of DBaaS providers, we identified the 12 most significant ones — Alibaba, Amazon, EnterpriseDB, Google, IBM, Microsoft, MongoDB, Oracle, Rackspace, Redis Labs, SAP, and Tencent — and researched, analyzed, and scored them. This report shows how each provider measures up and helps enterprise architecture (EA) professionals select the right one for their needs.
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For Enterprise Architecture Professionals
Advanced Level: Data Practices For Insights-Driven Businesses
May 9, 2019Noel Yuhanna
Business users want faster and easier access to trusted data to make accurate business decisions, while technology organizations want to simplify data management. Three years ago, Forrester invented the tech category "big data fabric" that addresses these goals and continues to evolve to support data democratization. Our updated big data fabric architecture, version 2.0, reflects new technology enhancements and highlights new opportunities for businesses. Enterprise architecture (EA) pros should use big data fabric to democratize data across the enterprise.
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For Enterprise Architecture Professionals
Leverage Tools To Minimize Risks And Accelerate Migrations
March 22, 2019Noel Yuhanna
Cloud databases have exploded on the scene as organizations look at faster and more scalable deployments and lower their costs. However, cloud database migrations are not simple lift-and-shift; they require careful planning, technical skills, and tools to succeed, especially when dealing with large and complex deployments. This report provides best practices to help enterprise architecture (EA) professionals manage a successful and less disruptive cloud database migration process.
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For Enterprise Architecture Professionals
The 15 Providers That Matter Most And How They Stack Up
March 14, 2019Noel Yuhanna
NoSQL has become critical for all businesses to support modern business applications. In our 26-criterion evaluation of NoSQL providers, we identified the 15 most significant ones — Aerospike, Amazon Web Services (AWS), ArangoDB, Couchbase, DataStax, Google, IBM, MarkLogic, Microsoft, MongoDB, Neo4j, Oracle, RavenDB, Redis Labs, and SAP — and researched, analyzed, and scored them. This report shows how each provider measures up and helps enterprise architecture (EA) professionals select the right one for their needs.
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For Enterprise Architecture Professionals
Road Map: The Data Management Playbook
November 20, 2018
Michele Goetz, Noel Yuhanna
Data bottlenecks create business bottlenecks. The days of provisioning data simply to meet the requirements of systems of record are over. Business stakeholders at the executive and line-of-business levels need data faster to keep up with customers, competitors, and partners. Information from the past won't support the insights of the future — businesses need real-time data. This report shows enterprise architects how they can use data to transform their organization and keep pace with the speed of business. This is an update to a previously published report; Forrester reviews and revises it periodically for continued relevance and accuracy.
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For Application Development & Delivery Professionals
Data Integration Technologies Evolve To Address New Challenges
February 4, 2010Noel Yuhanna, Rob Karel
Today, enterprises face increasing data integration challenges, largely because of growing data volumes, data protection issues, data migration complexities, the need for real-time information, integration of structured with unstructured data, and the limitations of existing data integration technologies. Business users want quick access to reliable real-time information to help them make better business decisions. As a result, information architecture and application development professionals find themselves on a never-ending quest to improve data's quality and timeliness. To provide insight into the vast array of options available to meet today's data integration challenges, Forrester investigated 11 technologies used to support a wide variety of data integration requirements, including change data capture (CDC), data access, data discovery, data quality services, data replication, data services platforms, distributed data caching, enterprise information integration (EII), enterprise services buses (ESBs), extract, transform, and load (ETL), and master data management (MDM). We found that data quality services, data services platforms, ESBs, and MDM continue to mature with widespread adoption, while CDC, data access, data replication, and ETL have reached the Equilibrium phase. Data discovery and distributed data caching are in the Survival phase, and EII stands alone in the Decline phase.
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For Enterprise Architecture Professionals
January 5, 2018
Brian Hopkins,
Michele Goetz, Noel Yuhanna
Your big data strategy is likely too little, too late. Customers are changing their expectations too quickly, and data lakes are becoming swamps. Insights-driven disruptors are using systems of insight to steal revenue from competitors and grow year-over-year at a double-digit pace. This report breaks down the components of a system of insight into a reference architecture and provides examples so enterprise architects can start helping their firms innovate their technology capabilities. This is an update to a previously published report.
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For Application Development & Delivery Professionals
IBM, Informatica, Composite Software, And Denodo Technologies Lead, With Microsoft And Red Hat Close Behind
February 10, 2010Noel Yuhanna, Mike Gilpin
In Forrester's 123-criteria evaluation of information-as-a-service (IaaS) — also known as data services — vendors, we found that IBM, Informatica, Composite Software, and Denodo Technologies led the pack because of strong data services features and capabilities such as data services modeling, real-time integration, data quality, and transformation, to support most use case scenarios. IBM, Informatica, and Composite Software have proven track records of supporting enterprisewide data services implementations. Denodo Technologies provides a broad set of data services features and capabilities and a strong delivery framework. Microsoft and Red Hat are Strong Performers; each offers a viable option, especially for customers considering a Microsoft stack or open source, respectively. Oracle no longer positions a product in the IaaS market despite having a leading IaaS product that it gained through acquiring BEA Systems in 2008.
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For Application Development & Delivery Professionals
Align Data Management Roles To Create Stronger Business Value
February 2, 2011Noel Yuhanna,
Gene Leganza, Rob Karel,
Boris Evelson, James G. Kobielus, Leslie Owens
The continuing explosion in data volume, increasing numbers of business users, growing data complexity, compliance requirements, need to support global operations, and growing need for real-time access are motivating enterprises to get more control of data management strategy and data architecture. More importantly, more and more businesses use insight derived from data as a key corporate asset for competitive differentiation. Enterprises need effective data management architecture to support their changing business requirements and ensure that they always use trusted and secure data for key processes. But myriad choices and new data requirements inundate data architects, enterprise architects, database administrators, and data quality specialists. Forrester's data management reference architecture provides a framework, including architectural patterns and building blocks, to guide these data management stakeholders in managing strategy and architecture.
