TDWI Analyst Research Team
Quality Content to Engage a Qualified Audience
In contrast to media companies that simply aggregate content from external sources, TDWI has a team of dedicated and respected analysts, faculty, writers, and editors who create the best analytics and data
management content available today. We focus on analyzing best practices and market research in data management, BI, and advanced analytics. Our quality content attracts a quality audience.
MEET THE ANALYSTS
Fern Halper, Ph.D., is vice president and director of TDWI Research for advanced analytics. She is well known in the analytics community, having published hundreds of articles, research reports, speeches, webinars, and more on data mining and information technology over the past 20 years. Halper is also co-author of several Dummies books on cloud computing, the hybrid cloud, and big data. She focuses on advanced analytics, including predictive analytics, social media analysis, text analytics, cloud computing, and big data analytics approaches. She has been a partner at industry analyst firm Hurwitz & Associates and a lead analyst for Bell Labs. Her Ph.D. is from Texas A&M University.
Philip Russom, Ph.D., is senior director of TDWI Research for data management and oversees many research-oriented publications, services, and events. He is a well-known figure in data management and business intelligence circles, having published numerous research reports, magazine articles, opinion columns, speeches, webinars, and more. Before joining TDWI in 2005, Russom was an industry analyst covering BI at Forrester Research and Giga Information Group. He also ran his own business as an independent industry analyst and BI consultant, and was a contributing editor with leading IT magazines. Before that, Russom worked in technical and marketing positions for various database vendors.
David Stodder is senior director of TDWI Research for business intelligence. He focuses on providing research-based insights and best practices for organizations implementing BI, analytics, data discovery, data visualization, performance management, and related technologies and methods. Stodder has provided thought leadership in BI, analytics, information management, and IT management for over two decades. Previously, he headed up his own independent firm and served as vice president and research director with Ventana Research. He was also the founding chief editor of Intelligent Enterprise, where he also served as editorial director for nine years.
Best Practices Reports
These quarterly reports present original, survey-based research on new technologies, concepts, and approaches. They provide a great opportunity for a limited number of sponsors to evangelize their latest solutions to the TDWI audience. Sponsors are involved in the research process, have distribution rights, and receive the leads from report downloads, webinar registrations, and on-demand webcast subscriptions.
2019 Best Practice Reports Topics and Schedule
|Cloud Data Management (CDM)
|Driving Business Transformation Using AI and Machine Learning
|Fast Decisions from Fast Data: New Technologies and Practices for Driving Out Data Latency
Custom Research Programs
TDWI provides custom research to sponsors to address specific technology messaging and best
practices. These programs include:
TDWI Checklist Reports provide a concise description of the best practices
required to succeed in a particular area of BI, analytics, or data management.
They outline six to eight best practices for data professionals and practitioners
who want to quickly learn how to succeed in a particular area of business. TDWI
Research analysts and faculty write the checklists, which synthesize their
experience and offer practical lessons that enable BI professionals to apply new
techniques to their projects or initiatives.
Custom Primary Research
TDWI analysts are experts in primary research. Historically, TDWI has surveyed our audience for
best practices research, benchmarking studies, and maturity models. New for 2018, TDWI will deploy
primary research to address specific sponsor needs such as positioning, product needs, or thought
leadership in a particular market space. TDWI analysts can provide feedback from the survey to
sponsors in one-on-one sessions. Alternately, primary research can drive custom content for sponsors.
If content is published, sponsors receive leads from downloads. Topics are determined by mutual
TDWI is known for producing the best maturity and readiness assessments in the
market. TDWI Readiness Assessments let business and IT professionals gauge
their organizations’ progress on their data and analytics journey. TDWI analysts
and faculty work with sponsors to develop custom assessments. Program sponsors
help shape the assessment model, questions, and the guide, and receive leads from
downloads. Past assessments include big data maturity, analytics maturity, IoT
readiness, and Hadoop readiness. Topics are determined by mutual agreement.
Introduced in 2017, TDWI Navigator reports help organizations understand specific
emerging markets and vendors that offer solutions in that market. These reports
provide an objective view of market trends, opportunities, and obstacles, and profile
vendor products. Sponsors receive leads from downloads and webcasts. Additionally,
individual profiles can be licensed separately as assets for sponsor sites.
Research Topics for 2019
Research topics for 2019 include but are not limited to:
- Modern data hubs, data requirements for IoT, AI and machine learning for data
management, modern metadata management, cloud-based data management,
multiplatform data architectures
- Open source for data management, the role of Hadoop in the mainstream, data lakes,
data warehouse modernization, analytics-driven data management, self-service data
access, real-time data
- Modern approaches to developing smarter applications, governance of self-service
applications, streamlining BI implementations, metadata and data cataloging,
developing an analytics culture, innovations in visual analytics
- Enterprise BI in a self-service world, reducing complexity in BI and analytics, search
and BI, self-service BI and visual analytics access to big data, real-time streaming,
AI and machine learning for smarter BI, data visualization and visual analytics, self-service data preparation
- AI/machine learning-enabled apps, deep learning, machine intelligence and
automation, open source for analytics
- Machine learning, NLP, predictive analytics, AI/cognitive systems, analytics in
the cloud, IoT analytics, data security analytics, organizational issues surrounding
advanced analytics and democratizing analytics