- log in
Posted by Boris Evelson on May 18, 2011
Forrester is in the middle of a major research effort on various Big Data-related topics. As part of this research, we’ll be kicking off a client survey shortly. I’d like to solicit everyone’s input on the survey questions and answer options. Here’s the first draft. What am I missing?
- Scope. What is the scope of your Big Data initiative?
- Status. What is the status of your Big Data initiative?
- In production
- Industry. Are the questions you are trying to address with your Big Data initiative general or industry-specific?
- Domains. What enterprise areas does your Big Data initiative address?
- Customer service
- Product development
- Brand management
- IT analytics
- Risk management
- Why BigData? What are the main business requirements or inadequacies of earlier-generation BI/DW/ET technologies, applications, and architecture that are causing you to consider or implement Big Data?
- Data volume
- Velocity of change and scope/requirements unpredictability
- Data diversity
- Analysis-driven requirements (Big Data) vs. requirements-driven analysis (traditional BI/DW)
- Cost. Big Data solutions are less expensive than traditional ETL/DW/BI solutions
- Data volume
- BigData as input to BI apps. Do you plan to use Big Data exploraton results for
- Inputs into BI applications
- Specifications for BI applications
- Types of data. What types of data/records are you planning to analyze using BigData technologies?
Transacational data from enterprise applications
Unstructured content from email, office documents, etc
Social media (Facebook, Twitter, etc) data
Sensor / Machine/Device Data
Image (large Video/Photographic) Data
- Ownership. Who owns or drives your BigData initiative?
- Mostly business-driven, with minimal IT support
- Business/IT collaboration
- Mostly IT driven, with minimal business involvement
- External assistance. Are you doing this on your own or with help of consultants and other external SMEs?
- All internal
- Mostly internal, with some help from third parties
- Mostly third parties under our direction and supervision
- All outsourced
- Integration with BI, DW, etc. How is your Big Data initiative integrated with, embedded in, or part of your other BI/DW/ETL/data governance/MDM initiatives, if at all?
- Big Data and BI/DW/ETL are just different areas of a broad information management activity
- Big Data and BI/DW/ETL are separate initiatives with close coordination
- Big Data and BI/DW/ETL are separate initiatives with some coordination
- Big Data and BI/DW/ETL are separate initiatives
- Integration with advanced analytics. How is your Big Data initiative integrated with, embedded in, or part of your other advanced analytics (statistical analysis, data mining, predictive modeling, etc.) initiatives, if at all?
- Big Data and advanced analytics are just different areas of a broad information management activity
- Big Data and advanced analytics are separate initiatives with close coordination
- Big Data and advanced analytics are separate initiatives with some coordination
- Big Data and advanced analytics are separate initiatives
- Project management. Do you run your Big Data initiative using the same or different PMO standards than BI/DW/ETL?
- Software development. Do you run your Big Data initiative using the same or different SDLC standards than BI/DW/ETL?
- Integration with enterprise apps. Do your Big Data applications stand on their own or are they tightly integrated or embedded with any of the following?
- Enterprise applications (ERP, CRM)
- Business processes (BPM)
- Business rules (BRE)
- Concerns. Are the following concerns higher, lower, or the same when dealing with Big Data initiatives as compared with earlier-generation BI/DW/ETL applications?
- Operational risk (liability, reputation, etc.)
- Retention. Do you intend to retain you raw Big Data post the exploration /analysis stage?
- Yes, for compliance
- Yes, for re-processing, more analysis
- Big Data technology. What technology do you use for BigData applications?
- Data integration tools based on BigData technology
- DW tools based on BigData technology
- BI tools based on BigData technology
- Advanced Analytics tools based on BigData technology
- App delivery model. Do you run your Big Data applications on premises or in the cloud?
- Hosted/private cloud
- Public cloud
- Commercial vs. Open Source. Do you use mostly
- Open source Big Data technology (Hadoop, MapReduce, Cassandra, and the other Apache open source specs)
- Commercial source Big Data tools
- Business case. Do you have a business case for the Big Data initaitive in place?
- Yes, with a proven ROI
- Yes, with a projected ROI
- Yes, with intangible benefits only
- No business case
- Metrics. How do you plan to measure the success of the Big Data inititative?
- With quantitative metrics tied to business performance
- With qualitative metrics tied to business performance
- With quantitative metrics tied to IT performance
- With qualitative metrics tied to IT performance
- No specific measurement methodology in place
Search Forrester's Blogs
Planning for innovation and risk in the wake of Brexit »
Blog: Go fast or go home
Why fast is the new normal for business technology strategy »
Forrester's CX Index
Predict how actions to improve CX will affect revenue performance.
Measure the customer experiences that matter most »
- Anjali Yakkundi (31)
- Art Schoeller (2)
- Boris Evelson (161)
- Claire Schooley (2)
- Clay Richardson (1)
- Diego Lo Giudice (23)
- Dominique Whittaker (4)
- Duncan Jones (1)
- Gene Cao (1)
- George Lawrie (19)
- Holger Kisker (38)
- Ian Jacobs (11)
- Jeffrey Hammond (31)
- Jennifer Belissent, Ph.D. (2)
- John Bruno (2)
- John R. Rymer (45)
- John Wargo (11)
- Jost Hoppermann (34)
- Kate Leggett (147)
- Kurt Bittner (4)
- Kyle McNabb (12)
- Leonard Couture (1)
- Liz Herbert (3)
- Margo Visitacion (9)
- Mark Grannan (11)
- Martha Bennett (13)
- Michael Barnes (21)
- Michael Facemire (18)
- Mike Gualtieri (118)
- Nick Barber (11)
- Noel Yuhanna (10)
- Paul Hamerman (2)
- Philipp Karcher (1)
- Randy Heffner (15)
- Rowan Curran (2)
- Stephen Powers (23)
- Ted Schadler (27)