Chapters 1 - 2: Specify the Question and Obtain Data

Business Value

All the items, events, and interactions that determine a company’s financial health; commonly measured by long-term profitability.

Business Process

A coordinated, standardized set of activities conducted by both people and equipment to accomplish a specific business task.

Business Analyst

A data specialist who curates and uses data to help an organization make effective business decisions.

Data Overload

Access or exposure to too much data; prevents data from being properly synthesized and interpreted.

Analytics Mindset

The willingness and ability to specify questions that need to be addressed, extract pertinent data, analyze it, and report results to decision-makers.

Data

Raw numbers and facts that have little meaning on their own.

Information

Data organized in a meaningful way in context; data with context.

Context

Setting, event, statement, or situation in which data can become more fully understood and evaluated.

Information Value Chain

The events and processes from data collection to information compilation to ultimate business decision.

Knowledge

Understanding or familiarity gained through learning.

Decisions

Conclusions reached after consideration of knowledge gained.

Data Scientist

A data specialist who knows how to work with, manipulate, and statistically test data.

Business Analytics

Use of data to make knowledge, draw conclusions, and address business questions.

Marketing Analytics

Use of business analytics to measure and improve marketing performance.

Financial Analytics

Use of business analytics to help a company measure, evaluate, and improve its financial performance.

Operations Analytics

Use of business analytics to measure and improve the efficiency and effectiveness of a company’s operations.

Accounting Analytics

Use of business analytics to evaluate financial performance and address accounting questions.

Relevant Data

Data directly or closely connected to the question being asked.

Reliable Data

Facts or truth with little or no bias.

Data Integrity

Combined accuracy, validity, and consistency of data stored and used over time.

Static Report

Not a constantly updated report of results.

Dynamic Report

Real-time updating report delivered through a dashboard.

Data Visualizations

Graphical representations of data that can reveal patterns and communicate findings.

Exploratory Visualizations

Graphical representation that uncovers patterns in data as part of descriptive or diagnostic analytics.

Enterprise System

Business management software that integrates applications from throughout the business into one system.

Relational databases

Compile data into separate tables to ensure completeness and avoid redundancy.

Big Data

Data sets that are too large and complex for existing systems to capture, store, manage, and analyze.

Structured data

Organized data that fits neatly in a table or database.

Unstructured data

Data without organization.

Semi-structured data

Data without internal structure but with tags or markers explaining what the data represents.

Internet of Things

A network of physical objects, such as cars and watches, that have sensors connecting them to the internet.

Data warehouse

A repository that integrates large amounts of structured data for reporting and analysis.

Data lake

A repository for both structured and unstructured data to be integrated for reporting and analysis.

OLAP (Online Analytical Processing)

Computing method that enables users to extract and query data for analysis from different points of view.

Distributed Computing

Data stored across multiple databases.

Raw Data

Data that has not been processed, cleaned, or aggregated.

Aggregated Data

Individual data points combined into subtotals.

Categorical Data

Data categorized into groups represented by labels.

Nominal Data

Categorical data that cannot be ranked but can be summarized through counting or grouping.

Ordinal Data

Categorical data that can be ranked and sorted.

Numerical Data

Meaningful numbers that represent quantities.

Interval Data

Data with no meaningful zero.

Ratio Data

Data with a meaningful zero, allowing for the calculation of ratios.

Data Completeness

Data is fully extracted from its original source.

Data Integrity

Data remains untampered with during extraction.