A finished DBA-833 Topic 2 data preparation decision log example, recording each cleaning choice for a late-delivery model with its reason, its effect on the data and the step that repeats it. Searches like "dba 833 topic 2 assignment example", "dba833 topic 2 sample" and "dba-833 topic 2 example" land here.
What a finished DBA-833 Topic 2 data preparation decision log looks like
The finished log treats preparation as part of the model rather than a chore before it. The broker wants to predict, at the moment a load is booked, whether it will arrive late, and its records hold several years of loads across a change of transportation management system. Each decision gets an entry. Loads re-tendered to a second carrier appear twice and are merged into one. Delivery times recorded in each carrier's local zone are converted to a single standard. Canceled loads are excluded, and the log states that this also removes loads canceled because they were already running behind. Missing equipment types are filled from each lane's usual pattern, with a flag kept so the model can see which values were inferred. Each entry reports how many loads and how many late arrivals the step removed or changed.
How a DBA-833 Topic 2 example is structured
The log opens with the prediction it serves, lateness forecast at booking, since what is known at booking limits which records and fields preparation may touch. A short section places preparation within the CRISP-DM process model, where it sits between understanding the data and modeling and is usually revisited more than once. The entries follow in the order the preparation code runs them. Each gives the decision, the reason, the loads and late arrivals affected, and whether the choice could plausibly move results. Choices that a reasonable analyst could make differently are marked as judgment calls, and two of them are rerun the other way to show the difference. A reconciliation then traces the load count from the raw extract to the modeling file, step by step. The log ends with a note on what the prepared file can no longer represent, such as loads the broker declined to book.
Preparation tied to the moment of booking
Only information the broker holds when a load is booked may survive preparation, so the log states that moment before listing a single cleaning decision.
Re-tendered loads merged into one
A load passed to a second carrier appears twice in the system, and merging the pair keeps one shipment from counting as two outcomes in the data.
An exclusion that removes late loads
Dropping canceled loads also drops some that were canceled because they were running behind, and the log reports how that step changes the observed late rate.
Inferred values flagged, never hidden
Equipment types filled from each lane's usual pattern carry an indicator, so the model and its readers can tell observed values from inferred ones.
Judgment calls rerun the other way
Two choices a careful analyst could reasonably reverse are run both ways, and the log reports whether either reversal changes which loads the model flags.
Counts traced from extract to file
A step-by-step reconciliation carries the raw extract down to the modeling file, so the silent loss of a region or a year would show up in the totals.
Where marks go in DBA-833 Topic 2
The largest loss here is a preparation section that says the data was cleaned and gives no entry for what cleaning meant. A reader cannot reproduce a result built on choices nobody recorded, and at the doctoral level an unreproducible result carries little weight. Exclusions described without their effect on the outcome rate are the next problem, because dropping canceled loads can quietly lower the share of late arrivals the model learns from. Imputation performed silently lets filled values pass as observations. Statistics for imputation or scaling computed on the whole file borrow information from the period later used for testing. Logs that present every choice as obvious hide the judgment calls a reviewer would most want to test, and a log with no load count reconciled from start to finish cannot show that nothing went missing.
Get a DBA-833 Topic 2 example written to your instructions
Send the DBA-833 Topic 2 instructions, your classroom rubric and a description of the dataset your section is preparing. A custom example is written to those criteria, with the prediction moment stated, every decision logged with its effect, inferred values flagged, judgment calls rerun and counts reconciled, returned in 24 to 48 hours. The first one is free.
DBA-833 Topic 2 questions, answered
Why does data preparation take so much of the effort?
Because operational records are collected to run a business, not to train a model. Shipments are re-tendered, systems change their field definitions, times are logged in different zones and some values are never entered. Each problem needs a decision, and each decision changes what the model will learn. Practitioners commonly describe preparation as the largest share of a project, which is why the course gives it a topic of its own.
Should preparation steps be fitted on all of the data?
No. Values used to fill gaps or rescale variables should be computed from the training data only and then applied to later records, because computing them across every record lets information from the test period shape the training file. Performance then looks better than the model will manage on new loads. The example computes each such value inside the training period and records that it did so.
What counts as a judgment call in preparation?
A choice on which careful analysts could reasonably differ, such as whether a delivery rescheduled by the receiver counts as late or whether an unusually long transit time is an entry error. The example marks those choices, reruns two of them the other way and reports whether results change. Showing that a conclusion survives a reversed choice is stronger evidence than asserting that the chosen option was correct.