| Course | BU 455 Big Data Management |
|---|---|
| Unit | Unit 1 |
| Paper type | Scale assessment |
| Length | About 880 words, 6 pages |
| Format | APA 7 student paper |
| School | Herzing University |
| Program | BS in Business Analytics |
| Updated | October 2026 |
Free sample paper for BU 455 Unit 1
About 85 Gigabytes a Year and 40 Messages a Second: A Scale Assessment of a Composite Bike-Share Operator's Data, Finding That Variety, Not Volume, Is Under Strain
Student Name
Business, Herzing University
BU 455: Big Data Management
Instructor Name
January 14, 2026
About 85 Gigabytes a Year and 40 Messages a Second: A Scale Assessment of a Composite Bike-Share Operator's Data, Finding That Variety, Not Volume, Is Under Strain
Why Measure Before Deciding
Pedalworks Mobility, a composite company created for this course, runs the bike-share system in a Pacific Northwest city of about 600,000 people under a contract with the city: 2,400 electric bikes, 900 conventional bikes and 310 docking stations. Its chief executive has been told by a vendor that the company has a big data problem and needs a big data platform. This assessment does not take the word big on trust. It measures the company's data against the three dimensions most often used to describe scale, volume, velocity and variety, first set out by Laney (2001), using figures rather than adjectives, states where each figure came from, and says which dimension is actually under strain.
Gandomi and Haider (2015) point out that there is no universal threshold above which data becomes big; what matters is whether the data's size, speed or diversity exceeds what an organization's current tools can handle. The question is therefore not whether Pedalworks' data is big in the abstract, but whether it strains the systems Pedalworks has: a single managed relational database, a reporting tool and one data engineer.
The Data Sources
Seven sources were identified by interviewing the operations, product and finance leads and examining the systems each uses. Figures are for the 2025 calendar year and come from system logs and storage reports, except where marked as estimates.
| Source | What it records | Records per year | Raw size per year | Form |
|---|---|---|---|---|
| Trips | Start and end station, times, rider account, fare | 1.9 million | About 2 GB | Structured rows |
| Bike telemetry | GPS position, battery, speed; every 30 seconds in use, every 15 minutes parked | About 184 million | About 37 GB | JSON messages |
| Station status | Bikes and empty docks at each station, every minute | About 163 million | About 16 GB | Structured rows |
| App events | Screens viewed, unlocks, errors | About 104 million | About 31 GB | JSON events |
| Payments | Charges and refunds, handled by a payment provider | 2.3 million | Under 1 GB | Structured rows |
| Maintenance tickets | Repairs, parts, mechanic notes | 41,000 | Under 1 GB | Rows with free text |
| Damage photos | Photos riders submit when reporting a problem | About 9,000 | About 18 GB (estimate from sample) | Images |
Volume
Adding the sources gives roughly 85 gigabytes of raw structured and semi-structured data a year, plus about 18 gigabytes of photos. Stored in compressed form, the structured data would take perhaps 15 to 20 gigabytes a year. Over the five years the city contract requires records to be available, raw data would reach about 425 gigabytes. That is a meaningful amount for a small company's single database to hold all at once, but it is well within what one modern server or managed database can store; it is far below the scale at which data must be spread across many machines simply to be kept. Volume is not under strain.
The largest source by rows is bike telemetry, which also dominates growth. A firmware update the bike maker has proposed would send position every 5 seconds instead of every 30 while bikes are in use. That would multiply in-use telemetry about sixfold and push annual raw volume to perhaps 250 gigabytes. The assessment notes this as the one change that could alter the volume verdict.
Velocity
Velocity concerns how fast data arrives and how fast the business needs to act on it. At the busiest moment of 2025, a warm Friday evening in July, about 1,100 bikes were in use at once. At one message every 30 seconds, that is about 37 telemetry messages a second, plus about 4 from parked bikes and 5 station updates a second: roughly 40 to 50 messages a second at peak. A single database can accept that rate comfortably, since it is far below the thousands of small writes a second that a managed relational database routinely handles.
What matters more is how quickly someone must respond. Rebalancing crews need to know within a few minutes when a busy station is full or empty, and the security lead wants to know within about a minute if a bike leaves the service area on a truck. Today those alerts come from a report run every 15 minutes, which is too slow. Velocity is therefore under mild strain: not because the data arrive too fast to store, but because some decisions need them faster than the current batch reports deliver.
Variety
Variety is where the strain is real. The company's data arrive in at least five forms: structured rows, JSON messages whose fields differ by bike firmware version, app events whose format changed twice in 2025, free-text mechanic notes and images. The telemetry alone has three different message layouts in circulation because not every bike has been updated, and a battery field that means percentage in one layout and volts in another. Analysts spend, by their own estimate, about a third of their time reconciling these formats before any question can be answered. Combining a damage photo, the mechanic's note about the same bike and the bike's telemetry before the damage is currently a manual task that takes an analyst most of an afternoon for a single incident, which is why it is rarely done.
Verdict
Measured against its own tools, Pedalworks does not have a volume problem, has a modest velocity need for a few operational alerts, and has a genuine variety problem. That verdict points away from the platform the vendor proposed, which is designed for data too large for one machine, and toward better handling of mixed formats and a small real-time alert path. The next unit tests whether the existing database can meet the requirements before anything else is considered. Kleppmann (2017) cautions that organizations often adopt distributed systems for scale they do not have and pay for the complexity without the benefit; this assessment gives Pedalworks the figures to avoid that. Pedalworks, its city and its data are invented for the course.
References
Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137-144. https://doi.org/10.1016/j.ijinfomgt.2014.10.007
Kleppmann, M. (2017). Designing data-intensive applications: The big ideas behind reliable, scalable, and maintainable systems. O'Reilly Media.
Laney, D. (2001). 3D data management: Controlling data volume, velocity, and variety (Application Delivery Strategies File 949). META Group.
What the BU 455 Unit 1 instructions ask for
The opening BU 455 unit asks students to assess whether an organization's data truly present big data challenges. Typical requirements include measuring the data's volume, velocity and variety with actual or estimated figures, stating the source of each figure, comparing the results with what the organization's current tools can handle, and concluding which dimension, if any, is under strain. When the case gives no volumes at all, instructors generally accept estimates drawn from comparable public systems, provided each one is labeled as an estimate. There is no universal threshold for big. Using an employer's real data volumes is discouraged. A source table with measured figures and a short APA 7 analysis of each dimension is typical.
How this BU 455 Unit 1 example is built
The paper begins with the company, the vendor's claim and the three dimensions, citing the source of the framework and the point that bigness is relative to tools. A table lists seven sources with what each records, annual records, raw size and form. The volume section adds them up, projects five years and names the firmware change that could alter the verdict. The velocity section calculates peak message rates and separates arrival speed from the speed decisions require. The variety section describes formats, layouts and the analysts' reconciliation time. The verdict section ranks the three dimensions and points the next unit toward testing the existing database.
Reading the BU 455 Unit 1 rubric
Herzing's rubric for the scale assessment usually rewards measured figures, stated sources, comparison with current capability, a clear verdict per dimension and awareness of future change, together with writing and APA. Measured figures earn full credit when each dimension is expressed in numbers such as gigabytes, records or messages per second. Sources score highest when each figure's origin is stated, including estimates. Comparison rewards judging the figures against the organization's actual tools. The verdict criterion pays for a separate conclusion on each dimension. Future change earns points when the assessment names what would alter its conclusion. Instructors often credit students who reach a modest verdict with evidence rather than confirming a vendor's claim.
Common BU 455 Unit 1 mistakes, and how to avoid them
Scale assessments commonly lose points by describing data as huge or fast without numbers. Another frequent problem is adding figures from sources without stating where they came from. Students often compare their totals with an arbitrary threshold instead of the organization's tools. Some treat all three dimensions as equally strained without evidence. Others ignore variety, which is often the real problem in small and medium organizations. Many never ask how quickly decisions actually need data, confusing arrival rate with required response time. A bike that reports every ten seconds does not mean a manager needs a ten-second dashboard, and that gap is where most of the verdict comes from. Finally, using what you know of your employer's data volumes can disclose confidential information; the case figures, or labeled estimates, demonstrate the method without that risk.
Get a BU 455 Unit 1 example written to your instructions
Email over the Unit 1 instructions with the BU 455 rubric your classroom carries and whatever case or scenario the assignment sets. We write a custom example that describes the workload first, measures each dimension with a derivation, treats platform limits as things to verify, and names the dimension actually under pressure. First custom sample free, back in 24 to 48 hours.
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BU 455 Unit 1 questions, answered
Where do the figures come from if the case does not supply them?
You construct them and say so. Take the operational description the assignment gives, reason from it to a records per period figure and a size per record, and show the arithmetic so a reader can follow it. Label the result as case material rather than presenting it as a measured fact. What loses credit is a number that appears with no derivation, since nobody can tell whether it was reasoned or chosen.
Is there a threshold above which data counts as big?
Not one you should state as fact, and a submission that names a fixed size is making a claim that ages badly. What a single ordinary machine can hold and process moves every year, so the sensible framing is relative: the workload is large when the approach already in place stops meeting the requirement. Say what the requirement is and the threshold question answers itself.
I know roughly how much data my employer handles. Can I use that?
Not as figures in a submission. Production data volumes, ingestion rates and the size of an internal store are commercially sensitive, and a graded document goes outside the company. Work from the case instead. Knowing the real order of magnitude will keep your constructed figures plausible, which is a genuine advantage, but the numbers on the page have to belong to the assignment.
Where can I find a free BU 455 Unit 1 sample paper?
The whole BU 455 Unit 1 scale assessment is free above, with the seven-source table, the three verdicts and margin notes. Assessing a different organization? Send the prompt and a matching assessment is written at no charge, generally inside two days.
Is there a size above which data count as big in BU 455 Unit 1?
No fixed threshold exists. The sample judges scale against the company's own tools, finding 85 gigabytes a year manageable for one database while variety strains how analysts work.