Business Intelligence vs. Business Analytics

A good place to start is understanding the differences between Business Intelligence and Business Analytics.  Business Intelligence (BI) involves the process of collecting data from various sources and preparing it for Business Analytics. Business Intelligence is more of a first step for companies to enable data-driven decisions. Business Analytics, on the other hand, is the analysis of the data provided by Business Intelligence. While Business Intelligence answers what happened, Business Analytics answers why it happened and whether it will happen again. Business Intelligence includes reporting, automated monitoring and alerting, dashboards, scorecards, and ad hoc query; Business Analytics, in contrast, includes statistical and quantitative analysis, data mining and predictive modeling.

If your business is still using spreadsheets, email, and PDF reports to share data and make decisions, then BI is a good place to start.

Do any of these statements resonate?

• We manually recreate a report every week, month, quarter using data from various sources.
• We ask the same questions about operations, sales, inventory, etc. month after month.
• We have some dashboards / reports but still map data from one form to another in excel.

Microsoft Power BI is one of the leading BI solutions. It is easy to use, affordable, highly reconfigurable and flexible. This makes it ideal for organizations looking to quickly implement BI without sacrificing key features.

Power BI uses datasets which you import / connect to. For example, customer data, sales data, financial, and internal supply chain data can all be connected to Power BI. The software comes in both on-premise and cloud service options, giving your organization flexibility.  

This data is then used to create reports. A report is a page or more of data visualizations – tables, charts, metrics, graphs, etc.  Since each dataset can be reused, the same data can appear on multiple reports.  Updating the underlying data can be automated to meet your needs. By joining and automating data from your various systems you create a centralized home for your data and allows your organization to focus on metrics important to success.

Every organization has the need gather, analyze, and interpret data in order to:

• Understand the past – which campaigns provided the best return?
• Optimize the present – which packaging provides the best lift in sales?
• Predict the future – which customers are likely to respond to this offer?

Getting Started

Start by looking around your organization places to improve performance by using:

• Operational Dashboards – used to optimize, track and monitor business processes.  They can organize data to make it easier for staff to perform their jobs and can provide metrics and KPIs.
• Analytical Dashboards – allow users to investigate trends, predict outcomes, and discover insights.  Analytical dashboards often include features like drill-down and ad-hoc querying.
• Strategic Dashboards  – used to monitor the overall status of an organization showing key performance indicators (KPIs). The data behind a strategic dashboard updates on a recurring basis, but at less frequent intervals than an operational dashboard.
• Automated Reporting –  Reports generated automatically behind the scenes to provide instant access to information from many data sources including drill down capabilities for additional details.

Napa Valley is home to some of the most beautiful wineries in the world. This data mashup uses multiple open data sources and to explore wineries in Napa:  

1. Napa County GIS data catalog (http://gis.napa.ca.gov/giscatalog/):
2. Global Wine Scores (https://www.globalwinescore.com/)
3. Napa Green (https://napagreen.org/)