Business Analytics · Beginner level

Beginner level · Module 3 of 5 · 10 guided hours

Data Quality and Comparison Analysis

Check data quality and compare performance fairly against targets, periods, peers and segments.

Learning objectives

  • Check data for completeness, accuracy and consistency
  • Make fair comparisons against targets, periods and peers
  • Segment data to find where differences arise

Topics

  • data quality dimensions
  • quick quality checks
  • comparison against target and previous period
  • like-for-like comparison
  • segmentation
  • averages and outliers

Lessons

  1. Lesson 1 Data Quality Checks

    Check that data is complete, accurate, consistent and timely before using it.

    completenessaccuracyconsistencytimeliness

  2. Lesson 2 Fair Comparisons

    Compare performance against targets, past periods and peers without misleading conclusions.

    actual vs targetperiod-on-periodlike-for-likerates vs totals

  3. Lesson 3 Segmentation and Simple Analysis

    Break results down by segment to see where performance differs and why.

    segmentationcontribution to changeaverages and outliersmix effects

Practical activity

Check a provided three-month data set for quality issues and compare branches against targets and each other, like for like.

Expected outcomes

  • Trustworthy data for analysis
  • Fair, insightful comparisons

Assessment

Quality and comparison analysis marked on issues found and fairness of comparisons.

Free taster lesson Data Quality Checks & Simple Analysis Read a free self-study lesson on this topic in the Free Course Library.

Taught live by an instructor — online or in person. Free course lessons are for self-study and do not lead to a certificate — see registration options.