1. Introduction to Business Data Analytics

Guide to Business Data Analytics

IIBA.org KnowledgeHub Guide to Business Data Analytics 1. Introduction to Business Data Analytics

Most business decisions involve some degree of uncertainty, and the decision-makers seldom know the exact outcome of their actions. Data plays a crucial and transformational role in how decision-makers view business uncertainties.

Data is a collection of unorganized facts or observations that can be processed to obtain valuable information. Analytics is the science of examining raw data and information in order to draw insights.

The volume of available data and the technical ability to quickly interpret insights from data are primary factors in reducing uncertainties in business decisions. Organizations are using data to improve their business processes and forecast typical business metrics, as well as support strategic decisions that shape their future.

Understanding and using business-relevant data is a means to obtain valuable insights to support more informed business decision-making. Organizations are investing in analytics initiatives to deliver on their strategic imperatives, innovate, and obtain competitive advantages in the marketplace. Such investments are driving the demand for skilled professionals with analysis and analytics knowledge and experience.

enabling new products and services and by creating new markets,
disrupting existing markets and unseating secure businesses,
driving increased efficiency (for example, for retailers to enable them to tailor products for customers),
identifying growth opportunities,
driving innovation,
operating more efficiently,
and improving risk management.

Business data analytics is an area of study that targets effective business decision-making as opposed to using the rigorous technical know-hows through which data is analyzed. Several business analysis tools, techniques, and competencies are used in business data analytics to direct analytics initiatives at many touch-points within the life cycle of an analytics initiative. This IIBA® Guide to Business Data Analytics emphasizes some of the significant business analysis and analytics concepts to build a foundational understanding that will guide practitioners through analytics initiatives.

Asking foundational questions to shape strategic imperatives:
- What will analytics initiatives and business data be used for?
- How will insights from data drive business outcomes and value for the enterprise?
- What type of business data is most likely to generate the insights needed?
- What business problems are being addressed using business data analytics?
- What is the hypothesis that will be tested?
- What do the identified patterns from data inform us about the future?
- Highlighting how enterprise data is organized and managed:
- What type of data is collected and captured?
- What are the primary data sources for the enterprise (for example, customer, supplier, or product data)?
- How are we managing data quality?
- What is the enterprise data strategy and architecture: legacy, data warehouse, data lakes and vaults, big data capable, and so forth?

How can analytics results be best explained (for example, data coherence versus storytelling)?
How are analytics results presented to stakeholders visually?
What business inferences can be drawn out of the data?

Enterprise business processes
What business processes and workflows are impacted?
If the analytics results drive change, how will that change be managed?
How does an organization become more data sophisticated?

What IT systems need to be improved to capitalize on the insights?
Are any additional technology/systems required?

Is additional training needed in order to improve employee capabilities?

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