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Introduction to Data Analytics

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01

Analytics Concepts

Measuring the chain from data to decision, and the decisions inside that chain, in numbers: the gap between the active subscriber counts computed from the same raw dataset with two defensible definitions, the data that descriptive, diagnostic, predictive, and prescriptive analytics require and the number of questions the dataset at hand cannot answer, how many steps the analysis workflow takes before it returns to the question, and how the same question turns into different output in the hands of a data analyst, a business analyst, and a data scientist.

  1. 01 What Is Data Analytics From a single subscriber table, the 'active subscriber count' is computed with three defensible definitions and yields three different numbers: 3,849 where the contract record is active, 3,548 where a reading was sent in the last 30 days, 4,211 where the contract is open. The totals of the first two definitions differ by only 301, yet they disagree on 645 subscribers; when the window, the one free number, is widened from 14 days to 90 days, the count rises from 1,859 to 3,750. No calculation changed, only the definition.
  2. 02 Types of Analytics The 16 questions put to the same subscriber table are split into descriptive, diagnostic, predictive, and prescriptive, and the number of answerable questions moves between 2 and 7 depending on two decisions. Counting derived fields as present opens 5 questions, and raising the history depth required for a predictive question from 3 periods to 12 closes 2 questions. The four questions of the prescriptive type open under none of the four decision combinations, because the table holds a record of what happened and no record of what was tried.
  3. 03 Analysis Workflow A workflow of five steps (question, data, analysis, finding, communication) is run together with 12 decisions: 10 of the decisions are seen after the step they belong to. When decisions are written as they are seen, the workflow produces 10 rework loops and 33 step visits; when every decision is written in its own step, it drops to 5 loops and 15 visits, and when a preview is added, to 1 loop and 8 visits. The one remaining loop does not close, because its content is not in the raw data but in the output of the analysis. When the accounting decision changes, the same workflow gives 15 visits instead of 33.
  4. 04 Analyst Roles A one-sentence question is given to three job descriptions, and the same table produces three different outputs: the measuring role reports -228 subscribers in 90 days (-5.14%), the decision-binding role gets -3.34% with the fee criterion and, since this falls short of the -5% threshold, takes no action, and the generalizing role gives two forecasts for one year ahead, between 2,191 and 3,286. Fee per subscriber has risen 1.89% from the same rows; of the three correct numbers, two show a drop and one shows a rise. Behind a one-sentence question stand 10 written decisions.

02

The Structure of Data

Counting what kind of thing the data being worked on is and which summaries that makes legitimate: the meaningless average produced by treating a discrete field as continuous, the summaries that nominal, ordinal, interval, and ratio scales permit, a primary and a secondary source giving different numbers for the same quantity, the number of rows eliminated by accuracy, completeness, consistency, and timeliness thresholds, the question that should not be asked even though the data can answer it, and the breakdown that descends to a single person.

  1. 01 Data Types Eight fields of 1,400 subscriber records are stored as numbers and all eight get an average, but three of them are qualitative: the average of the region code comes out 3.19 under the register coding and 2.69 under the size coding, and not a single record in the data has changed. No single record equals the 1.20 average of the discrete visit field, and 68.3% of the records fall below that average; when the continuous consumption field is rounded to 5 m³ steps the total shifts by only 1.4 per thousand, yet 229 records change tariff tier.
  2. 02 Measurement Scales Ten fields are placed on four scales and all 40 cells formed by multiplying them with four summaries are computed: 28 turn out to be legitimate, and 12 are numbers that were computed but that the scale does not support. Two defensible codings given to the ordinal satisfaction field — 1, 2, 3, 4, 5 and 0, 4, 6, 7, 8 — reverse the ranking of the regions: the first region falls to fifth without a single grade changing. On an interval scale the ratio of the same two readings falls from 4.67 to 1.08 when the zero point changes, while their difference stays fixed at 22.0 units.
  3. 03 Data Sources The same quantity — average monthly consumption — gives three different numbers from three sources: 22.42 m³ from the field survey, 21.59 m³ for the value rebuilt from the billing summary, 17.01 m³ from meter telemetry, while the model's true value is 21.31 m³. Even the subscriber count comes out 1,400, 886, and 1,041 depending on the source. When a single decision is changed in each source, the six numbers spread between 14.11 and 22.42 m³ and none of them contains a calculation error; the source of the bias is visible in the coverage table.
  4. 04 Data Quality Dimensions Each of the four quality dimensions gives a number: 46 records carry physically impossible readings, 200 records have an empty required field, 104 records have a tier field that contradicts the reading, 482 records are older than 90 days, and 730 records pass all four rules. As the threshold tightens, 1,400 rows fall to 422 and the reported mean drops from 24.70 to 20.83 m³, crossing the model's true value of 21.31 once on the way; the eliminated rows are not random, and 88.2% of the top tariff tier is eliminated.
  5. 05 Data Ethics and Privacy Of 18 questions asked of the same subscriber set, 14 can be answered with the fields on hand and 4 have no field; when the boundary rule changes, the number of questions that are answerable but should not be asked rises from 3 to 8 and the reportable questions fall from 11 to 6. As the breakdown deepens the group shrinks: the smallest group is 209 records in the region breakdown and 1 record in the four-field breakdown, and 45 subscribers sit alone in a cell. When the minimum group size threshold is raised from 5 to 10, the suppressed cells rise from 117 to 146 and the records left outside the report from 245 to 431.

Final exam

Introduction to Data Analytics — Final Exam

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