Big Data integrity / fundamentals

BDPC · 30 questions

• A county assessor's office still runs property rolls in a single relational database. Staff ask when their workload becomes Big Data instead of ordinary reporting. Which condition best marks that shift?
• A city manager wants one council-ready sentence defining Big Data beyond "lots of data." Which definition fits CertiProf BDPC fundamentals?
• A municipal utilities board asks what business benefit they should expect if they invest in Big Data analytics for outage patterns. Which benefit is the soundest expectation?
• A library consortium compares nightly batch SQL reports on catalog tables with a new workload that analyzes clickstreams and sensor feeds together. How do those workloads differ in Big Data terms?
• A parks department debates whether Big Data applies only to an enterprise-wide Hadoop program or also to a departmental analytics effort on semi-structured reservation and IoT feeds. Which view matches BDPC scope thinking?
• A public-health analyst worries that dashboards look precise while underlying citizen surveys are incomplete. Which integrity principle should guide the team?
• A 311 center hears about cognitive systems trained on huge corpora of documents and interactions and wonders what Big Data problem class that pattern illustrates. Which characterization is most accurate for BDPC fundamentals?
• A regional transit agency asks which operational domains sit inside Big Data's practical reach. Which answer best reflects BDPC breadth?
• A wastewater SCADA historian grows by terabytes of sensor readings each month, and the warehouse team hits storage and query walls on the conventional platform. Which of the 4 V's is primarily illustrated?
• A traffic-management center needs curb-lane occupancy updates every few seconds rather than overnight batches. Which of the 4 V's does this requirement primarily stress?
• An emergency-management office mixes CAD logs, radio transcripts, map layers, and smartphone photos after a storm. Which of the 4 V's does this mix primarily illustrate?
• A housing authority distrusts scraped rental listings that conflict with permit records. Which of the 4 V's is the central concern?
• A smart-city pilot claims "we have Big Data" because cameras exist. Staff must map which of the 4 V's actually stress their stack. Which approach is most aligned with BDPC fundamentals?
• A clerk assumes any JSON API feed is "volume" when the real pain is dozens of drifting schemas across partners. Which correction is accurate?
• A flood-alert team wants instant social posts on the operations dashboard, but analysts flag rumor risk. Which 4 V tension should leaders recognize?
• A mayor's innovation office lists predictive maintenance, citizen sentiment analysis, and dynamic routing as candidate pilots. What Big Data rationale best justifies treating them as application classes?
• A CIO asks what "managing Big Data" includes beyond buying disks. Which answer matches BDPC fundamentals?
• A mid-size city sketches an ecosystem diagram and places a serving dashboard in the ingestion layer while putting Kafka-style collection in the serving layer. Which correction reflects conceptual ecosystem roles?
• A budget office wants analytics that find cost drivers across multi-year procurement files plus IoT meter data. What is the primary purpose of that Big Data analysis?
• Transit supervisors want a wallboard of live vehicle and delay indicators rather than weekly PDF summaries. What Big Data serving pattern does this request represent?
• IT lists failures including schema drift, cluster cost overruns, skill gaps, and batch windows too slow for same-day decisions. What do these illustrate in BDPC terms?
• After naming challenges, the team maps remedies: distributed storage for scale limits, parallel processing for slow jobs, NoSQL for flexible structures, streaming for timely signals, and cloud elasticity for spiky demand. Which statement best captures the BDPC skill being practiced?
• Finance prefers vertically scaling one large SQL server; engineering argues for horizontal Big Data patterns for clickstream and sensor mashups. Which comparison is most accurate?
• Public works assumes vendors "guarantee" sensor truth, yet analysts still validate anomalies before publishing street-condition scores. Which veracity operations principle applies?
• A three-person grants office maintains a tidy 50,000-row spreadsheet that conventional tools handle comfortably and asks if they need a Hadoop cluster. What is the best BDPC-aligned answer?
• A city council plans zoning changes and wants mobility traces, 311 complaints, and census tables mashed together before voting. What Big Data benefit is the council primarily seeking?
• A water-plant modernization pitch cites Industry 4.0 and continuous sensor floods from pumps and valves. How should staff correctly tie that pitch to Big Data fundamentals?
• A vendor demo sells one appliance as ‘the entire Big Data ecosystem.’ What should municipal architects emphasize instead?
• Solid-waste managers believe truck miles would drop if stop-level service data and live traffic were analyzed together. Which Big Data benefit does that goal illustrate?
• Emergency managers face conflicting reports across radio, apps, and sensors and want faster situational awareness. What Big Data stance best fits?