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For Enterprise Architecture Professionals
The 14 Providers That Matter Most And How They Stack Up
October 29, 2018Noel Yuhanna
Cloud data warehouse (CDW) deployments are on the rise as firms look at lowering costs, supporting new accelerated insights, and simplifying data management. In our 25-criterion evaluation of CDW providers, we identified the 14 most significant ones — Alibaba, Amazon Web Services (AWS), Exasol, Google, Hortonworks, Huawei, IBM, MarkLogic, Micro Focus, Microsoft, Oracle, Pivotal, Snowflake, and Teradata — and researched, analyzed, and scored them. This report shows how each provider measures up and helps enterprise architecture (EA) pros make the right choice.
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For Enterprise Architecture Professionals
Forrester's Overview Of 18 Hadoop/Spark Platform Providers
July 20, 2018Noel Yuhanna,
Mike Gualtieri
You can use Hadoop/Spark (HARK) platforms to access open source innovation, become significantly more productive, and foster collaboration. But to access these benefits, you'll first have to select from a diverse set of vendors — vendors that vary by size, functionality, geography, and vertical market focus. Enterprise architecture (EA) professionals should use Forrester's Now Tech report to understand the value they can expect from a HARK platform provider and select vendors based on a tool-set approach.
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For Enterprise Architecture Professionals
Tools And Technology: The Data Management Playbook
June 12, 2018Noel Yuhanna
Big data fabric, an emerging platform, accelerates insights by automating ingestion, curation, discovery, preparation, and integration from data silos. Forrester identified the 15 most significant big data fabric vendors — Cambridge Semantics, Cloudera, Denodo Technologies, Hitachi Vantara, Hortonworks, IBM, Informatica, Oracle, Paxata, Podium Data, SAP, Syncsort, Talend, TIBCO Software, and Trifacta — and researched, analyzed, and scored them against 26 criteria. This report shows how each vendor measures up and helps EA pros make the right choice.
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For Enterprise Architecture Professionals
Forrester's Overview Of 18 Big Data Fabric Vendors
April 17, 2018Noel Yuhanna
You can use big data fabric to provide a comprehensive view of data resources, secure big data sources, and accelerate big data initiatives. But to access these benefits, you'll first have to select from a diverse set of vendors — vendors that vary by size, geography, and vertical market focus. Enterprise architecture (EA) professionals should use Forrester's Now Tech report to understand the value they can expect from a big data fabric provider and select vendors based on size.
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For Enterprise Architecture Professionals
Forrester's Overview Of 15 Cloud Data Warehouse Vendors
March 13, 2018Noel Yuhanna
You can use cloud data warehouses (CDWs) to build data warehouses more quickly, support new business use cases for DWs, and lower infrastructure and software cost. But to access these benefits, you'll first have to select from a diverse set of vendors — vendors that vary by size, functionality, geography, and vertical market focus. Enterprise architecture (EA) pros should use Forrester's Now Tech report to understand the value they can expect from a CDW provider and select vendors based on size and functionality.
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For Enterprise Architecture Professionals
Road Map: The Data Management Playbook
November 7, 2017
Michele Goetz, Noel Yuhanna
Data bottlenecks create business bottlenecks. The days of provisioning data to simply 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 from turtle to hare 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 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.
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For Enterprise Architecture Professionals
Advanced Level: Technology Practices For Insights-Driven Businesses
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.
