How to use weather data in landscaping and lawn care businesses

Landscaping and lawn care businesses have a great opportunity to use quality weather data in an automated way to improve their efficiency, drive customer satisfaction, and increase profits. Common wisdom suggests that only larger organizations can afford to access automated weather data services, and smaller businesses are stuck watching the nightly TV weather person to …

Using Weather Data in Business Intelligence – Part 3

How to make intelligent decisions using BI and weather forecasts

Now, armed with the insights that we found in part two, we are ready to apply those insights using weather forecasts. As we did when analyzing our historical business records using weather history, we will use the high-quality weather data service that we identified in part one of this article series. Then, we will join this data with our business locations. Only this time, instead of finding existing patterns we will apply the patterns discovered to make more intelligent decisions.

Using Weather Data in Business Intelligence – Part 2

How to analyze business data using historical weather records

In this article we will continue where part one stopped. Once high-quality, BI-friendly weather data has been found, we next need to understand how it can be used to analysis historical business data, Most business intelligence systems have a warehouse containing years of business records including locations and dates. This article will show how to match those records to weather data and identify useful patterns and trends.

Using Weather Data in Business Intelligence – Part 1

How to find weather data that works well with business intelligence analysis

In this series of three articles we will first discuss how to find weather data that is compatible with both your existing business data and your existing business intelligence systems. Then, in part two we will discuss strategies to analyze historical weather data in conjunction with your BI tools and with your data. Finally, part three will discuss how to apply the insights learned from the historical analysis to make more intelligent decisions using business patterns and weather forecast data.