A Beginner’s Guide to Google Business Intelligence Certificate: Key Terms Explained

Google Business Intelligence Certification — Foundational Concepts

Data government professionals

are responsible for the formal management of an organization’s data assets

Application Programming Interface (API)

A set of functions and procedures that integrate computer programs, forming a connection that enables them to communicate

Data Warehousing Specialists

People who develop processes and procedures to effectively store and organize data

Information Technology Professionals (IT)

People who test, install, repair, upgrade, and mention hardware and software solution

Project Managers

People who handle the day-to-day project steps, scope, schedule, budget, and resource

Data Maturity

The extent to which an organization is able to effectively use its data in order to extract actionable insights.

Data Life Cycle

The sequence of stages that data experiences, which include plan, capture, manage, analyze, archive, and destroy.

Data Analysis Process

The 6 phases of ask, prepare, process, analyze, share, and act.

Data Strategy

The management of the people, processes, and tools used in data analysis.

Business intelligence

focuses on data maturity and emphasizes sustainable, reusable methods and tools.

Data analysts

examine data through a specific topic or subject-matter lens and provide targeted insights rather than broad monitoring or management.

Business Intelligence Stages

1. Capture: What happen?
2. Analyze: What did it happen?

• Discover key relationships between data points
• Identify connections that were not easily apparent
• Understand why something happened

3. Monitor: What’s happening now?

• Gain insights about what’s happening in the organization right now
• Building and using hardware and software tools to easily and rapidly analyze data and enable stakeholders to make impactful business decisions.

Business Intelligence Strategy

The management of people, processes, and tools used in the business intelligence process.

Business Intelligence Government

A process for defining and implementing business intelligence systems and frameworks within an organization.

• What is the vision for the business intelligence process?
• How does that vision align with current business strategy?

Business Intelligence Professionals

continually monitor process and systems to determine if it’s necessary to make updates for greater efficiency and optimization

=> bring the current state closer to the ideal state

=> BI Professionals do this through a process called gap analysis, which is method for examining and evaluating the current state of a process in order to identify opportunities for improvement in the future

=> BI Professionals need ways to share and communicate plan, updates, and summaries about projects. A common document called an executive summary is used to update decision makes who may not be directly involved in the tasks of a project.

• An executive summary is a document that collects the most important points contained in a longer plan or report.

Context

The condition in which something exists or happens

Knowing this context, the BI professional working on this project is able to build out appropriate metrics, reporting tables, and the dashboard that tracks that metric in a way that helps stakeholders make informed decisions about this process.

To achieve business goals in an organization, we need to begin with the Stakeholder Requirements, Project Requirements, and Strategy documents as the foundation for our business intelligence work.

Stakeholder Requirements Document

The Stakeholder Requirements Document enables we to capture stakeholder requests and requirements so we understand their needs before planning the rest of the project details or strategy.

Project Requirements Document

Once we have established the stakeholder requirements, we can start thinking about the project requirements that need to be met to achieve the stakeholder requirements.

Strategy Document

The Strategy Document is a collaborative place to align with stakeholders about project deliverables. We will work together to establish information about dashboard functionality and associated metrics and charts.

When we ask questions, they need to be SMART questions.

• Specific: Does it address the problem? Does it have context?
• Measurable: Will the question give you answers that you can measure?
• Action-oriented: Will the answers provide information that helps you advise some type of plan?
• Relevant: Is the question about the particular problem you are trying to solve?
• Time-bounded: Are the answers relevant to the specific time being studied?

Before learning business intelligence, there are some terms we need to know: Data Availability, Data Model, Data Pipeline, ETL, and Data Visualization.

Data Availability

The degree to which timely and relevant information is readily accessible and can be effectively used.

Data Availability Factors:

• Data integrity: the accuracy, completeness, consistency, and trustworthiness of data throughout its life cycle.
• Data visibility: the degree or extent to which information can be identified, monitored, and integrated from disparate internal and external sources.
• Update Frequency: How often disparate data sources are being refreshed with new information
• Change: The process of altering data, either through internal processes or external influence.

Data Model

A tool for organizing data elements and how they relate to one another.

Data Pipeline

A series of processes that transports data from different sources to their final destination for storage and analysis

ETL

A type of data pipeline that enables data to be gathered from source systems, converted into a useful format, and brought into a data warehouse or other unified destination system.

=> The process of ETL plays a key role in data integration because it enables business intelligence professionals to role

Data Visualization

The graphical representation of data

• Dashboard: An interactive visualization tool that monitors live, incoming data

Iteration

Repeating a procedure over and over again in order to keep getting closer to the desired result.

Data Science

A field of study that uses data to create new ways of modeling and understanding the unknown

• Qualitative Data: measures qualities and characteristics
• Quantitative Data: measures numerical facts

When collecting data for study, what are some reasons to consider sample size?

1. Collect data that represents a diverse set of perspectives
2. To make sure a few unusual responses don’t skew results

Metadata

is data about data, which helps people communicate about data across the business and makes it easier to reuse.

There are 3 common type of metadata:

1. Descriptive metadata: describes a piece of data and can be used to identify it at a later point in time (e.g., a library ISBN).
2. Structural metadata: indicates how a piece of data is organized and whether it is part of one or more data collections (e.g., the content of a book).
3. Administrative metadata: indicates the technical source of a digital asset (e.g., photos on a phone).

Here, we’re going introduce other relevant terms in the business intelligence field.

Bias

A conscious or subconscious preference in favor of or against a person, group of people or thing.

Metric

A single, quantifiable data point that is used to evaluate performance.

Here are some examples below:

• A restaurant’s customer loyalty rate
• A manufacturing team’s productivity levels
• A fitness center’s monthly profits and losses
• The amount of inventory in a pharmacy’s warehouse

Metrics best practices:

• Limit the number of the metrics: More information is NOT always better
• Make sure metrics are aligned with business objectives
• Confirm that the necessary technologies and processes are in place
• Use SMART methodology

North Star Metric

The company’s North Star Metric goes beyond short-term goals: it’s intended to capture the core measurable value of a business’s products or services over its entire lifetime.

Here are 3 main advantages of using the North Star Metric:

1. Cross-team alignment: it allows all of the teams to have a consistent goal to focus on, even as they work on different things.
2. Tracking growth: provides a long-term measurable data point that stakeholders can focus on when discussing overall performance and growth in a business.
3. Focusing values: it determines what is important to the organization and stakeholders

Key Performance Indicator (KPI)

A quantifiable value, closely linked to business strategy, which is used to track progress toward a goal

Metrics support KPIs, and KPIs support overall business objectives.