Business Intelligence (BI) refers to the technical infrastructure for collecting, storing, and analyzing company data. It aims to provide actionable insights to executives and managers to arm them for better-informed decision-making.
BI can appeal to organizations that feel they lack the information needed to make key decisions for their company’s future. However, implementing BI is not like flipping a light switch. This article covers the work that must be done before moving forward with a business intelligence tool.
This one sounds like a given, but it’s intricate. Data is the foundation of success for any reporting solution. High-quality data is accurate, consistent, complete, and relevant to the objectives set forth by a business. Reliable data ensures reports and dashboards in a business intelligence tool are based on factual information, minimizing the risk of misguided decisions. Consistency is key for drawing meaningful comparisons overtime, enabling an organization to track trends, identify patterns, and measure performance accurately.
Completeness and relevance go hand-in-hand. A company must have all the necessary data that contributes to decision-making without having excess data that’s irrelevant. An organization should determine internally what data is needed to make decisions before implementing a BI tool. Reliable data is the foundation upon which BI is implemented.
Data governance encompasses the comprehensive management of data’s availability, usability, integrity, and security across an organization.Data is not a one-and-done job. The process of entering, storing, maintaining, and auditing data is continuous. An effective governance model clearly defines roles and permissions by specifying who can access, create, or modify data.
Data governance also focuses on safeguarding data and ensuring compliance with relevant regulations and standards (GDPR, HIPAA, etc.). This involves implementing policies and procedures to protect data from unauthorized access, breaches, and misuse. Employees are trained in the proper use of company devices and best practices for avoiding security vulnerabilities.
Even the most sophisticated BI tool cannot overcome a poorly designed data governance model. Decision-makers can rest assured knowing the data that drives reports and dashboards has been properly managed when an effective data model has been enacted.
A department store database, for example, has multiple tables. There is a “fact” table that holds a list of events, along with “lookup”tables which store descriptive information about the events in the fact table. In the example, the fact table is a list of transactions with information such as transaction ID, customer ID, and product ID. There’s a customer lookup table that stores customer name, address, and other personal information, as well as a product lookup table that stores product name, brand, and unit price.
Data models are the bridge between raw data and visualizations in a business intelligence platform. A data model defines the relationships between sets of data or between the fact table and its corresponding lookup tables. The model enables companies to “slice and dice” by different variables to draw insights. A company must define, or at least understand, how its data is connected prior to moving forward with BI.
Business Intelligence is not a quick fix to a company’s problems. Implementing BI tools demands significant investment in terms of time, personnel, and money. The implementation typically spans four to twelve weeks, which includes developing dashboard mockups, cleaning and validating data, designing data wireframes, and constructing reports and dashboards.
Business intelligence is designed for ongoing, strategic data analysis rather than ad-hoc reporting. Expertise in BI platforms is less common than in tools such as Microsoft Excel, necessitating dedicated internal resources or experienced consultants. This brings us to our final key resource:money. Costs include either a fixed-price or subscription-based model, building the tools, and ongoing data storage fees.
Business intelligence can be successfully implemented when quality data is in place, a proper data governance model maintains data integrity, and proper resources are allocated. In a data-driven business environment, it may be time to begin evaluating the IT department in preparation for a BI implementation. If your organization is preparing for business intelligence or needs help implementing a BI tool, our team can help guide you through the process. Reach out to us at info@trenegy.com for more information.
Trenegy is a non-traditional consulting firm based in Houston, Texas.