A short, focused reference for business analytics students and professionals who aren't technical specialists but need to speak the language of data.

What's inside:

• Types of analytics: descriptive, diagnostic, predictive, prescriptive, real-time, embedded and geospatial analytics, plus people and marketing analytics

• Data fundamentals: structured vs unstructured, cross-sectional vs time series, the 4 V's of big data, a data unit conversion table

• Statistics: mean, median, mode, range, variance, standard deviation, frequency distributions

• BI and infrastructure: data lakes and warehouses, governance, integration, ingestion, catalogues, democratisation

• Data-driven decision making: the 6-step DDDM process

• Text mining: tokenisation, stemming, corpus, term-document matrix, sentiment analysis

• Decision and risk analysis: payoff tables, decision trees, chance nodes, expected value

• Visualisation and dashboards: when to use each chart type, sparklines, histograms, static vs dynamic dashboards

• Privacy: privacy calculus, the privacy paradox, GDPR