Big Data

Measured in terms of volume, velocity, and variety, big data represents a major disruption in the business intelligence and data management landscape, upending fundamental notions about governance and IT delivery. With traditional solutions becoming too expensive to scale or adapt to rapidly evolving conditions, companies are scrambling to find affordable technologies that will help them store, process, and query all of their data. Innovative solutions will enable companies to extract maximum value from big data and create differentiated, more personal customer experiences.

Latest Research

For Enterprise Architecture Professionals

REPORT: Now Tech: Hadoop/Spark Platforms, Q3 2018

Forrester's Overview Of 18 Hadoop/Spark Platform Providers

July 20, 2018 Noel 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.
For CIO Professionals

REPORT: Use IoT To Link Physical Operations And Digital Business

Integrated Systems Of Insight Create Competitive Advantage

July 18, 2018 Brian Hopkins, Frank E. Gillett

In many companies, internet-of-things (IoT) projects are isolated, with no connection to digital business initiatives. Companies miss out on combining real-world insights with digital business processes. Even when IoT data is integrated with digital systems, today's big data analytics approaches can't support real-time insight and action. The CIOs that do integrate IoT-enabled physical processes with digital systems will create big competitive advantages. This report shows how systems of insight, connected via microservices, can help you become a leader.
For Enterprise Architecture Professionals

REPORT: The Forrester Wave™: Machine Learning Data Catalogs, Q2 2018

The 12 Providers That Matter Most And How They Stack Up

June 21, 2018 Michele Goetz

In our 29-criteria evaluation of machine learning data catalogs (MLDCs) providers, we identified the 12 most significant ones — Alation, Cambridge Semantics, Cloudera, Collibra, Hortonworks, IBM, Infogix, Informatica, Oracle, Reltio, Unifi Software, and Waterline Data — and researched, analyzed, and scored them. This report shows how each provider measures up and helps enterprise architecture (EA) professionals make the right choice.
For Enterprise Architecture Professionals

REPORT: The Forrester Wave™: Big Data Fabric, Q2 2018

The 15 Providers That Matter Most And How They Stack Up

June 12, 2018 Noel 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.
For Enterprise Architecture Professionals

REPORT: Now Tech: Big Data Fabric, Q2 2018

Forrester's Overview Of 18 Big Data Fabric Vendors

April 17, 2018 Noel 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.