Business intelligence is a term that covers the processes and methods of collecting, storing, and analyzing data from business operations or activities to optimize performance. All disparate information comes together to create a comprehensive view of a business to help people make better, actionable decisions. Over the past few years, business intelligence has evolved to include more processes and activities to help improve performance.
BI has a history as a buzzword that originally emerged in the 1960s as a system of sharing information across organizations. Over the years it has grown alongside computer models for decision-making and turning data into insights before becoming specific offerings from BI teams with IT-reliant service solutions. Modern BI solutions prioritize flexible self-service analysis, governed data on trusted platforms, empowered business users, and speed to insight.
There are many terms and technologies included in Business Intelligence. The below bullet points include some but certainly not all of the terms. As you would imagine in IT these terms change daily and also from vendor to vendor. The basics are:
- Data mining: Using databases, statistics and machine learning to uncover trends in large datasets.
- Reporting: Sharing data analysis to stakeholders so they can draw conclusions and make decisions.
- Performance metrics and benchmarking: Comparing current performance data to historical data to track performance against goals, typically using customized dashboards.
- Descriptive analytics: Using preliminary data analysis to find out what happened.
- Querying: Asking the data specific questions, BI pulling the answers from the datasets.
- Statistical analysis: Taking the results from descriptive analytics and further exploring the data using statistics such as how this trend happened and why.
- Data visualization: Turning data analysis into visual representations such as charts, graphs, and histograms to more easily consume data.
- Visual analysis: Exploring data through visual storytelling to communicate insights on the fly and stay in the flow of analysis.
- Data preparation: Compiling multiple data sources, identifying the dimensions and measurements, preparing it for data analysis.
There is also the why we use Business Intelligence in the Digital Revolution.
- Identify ways to increase profit
- Analyze customer behavior
- Compare data with competitors
- Track performance
- Optimize operations
- Predict success
- Spot market trends
- Discover issues or problems
In Agribusiness the need for Business Intelligence mirrors other businesses. Depending on where your company is on the technology scale will determine the tools you need to move forward in today’s business environment. We have information silos in our internal business applications as well as the supply chain. The Internet of Things, IoT, is bringing data silos together for a more holistic view of the information required to grow the business.
Let the Beyond team bring Microsoft Power BI to your Agribusiness.