The field of data analytics is primarily focused on finding answers to questions that affect a business or company. This process involves devising methods to process, clean, and organize structured data so that statistical analyses can be run and key insights can be extracted. By finding answers to these questions, a Data Analyst can produce actionable insights that yield immediate professional improvements, as well as solutions that may benefit a company or organization for years to come. This process typically involves using a combination of computer programming, statistical analysis, and data visualization software.
There are four kinds of data analytics: descriptive, diagnostic, predictive, and prescriptive, which can be used independently or together, to help a business or an organization perform its analytics needs on data. Predictive analytics draws on the summarized data, as well as past trends and behaviors, to offer logical predictions on what may occur in the future. This branch of analytics uses statistical modeling to make forecasts that seek to answer the question: “What happens if?” The accuracy of these forecasted estimates depends on the quality of the data.
Predictive models have many real-world applications. They are used on a daily basis for sales forecasting, risk assessment and mitigation, sports analytics, and fraud detection. Predictive analytics informs video game development, and customer service decisions, as well as other future-looking products or services.
This article will explore the integral role data analytics, and in particular predictive analytics, plays in weather forecasting.
Benefits of Using Data Analytics to Predict the Weather
Predicting the weather is no easy task. The process of forecasting what the weather will bring is a very complex process that draws from data that comes from many sources, as well as an array of analyses and weather models that are offered in an attempt to make sense of the onslaught of data. Many tools and instruments are used in this process, such as barometers, thermometers, weather balloons, and even deep-space satellites.
The amount of available data can be both a blessing and a curse. While it’s important to have extensive data from many sources to gather accurate information and offer pointed predictions, it can be complicated to select which weather models are most applicable to the data at hand. In addition, the further into the future a forecast is made, such as a week out or even longer, variables such as the constantly changing atmosphere can complicate matters. This is why continuous, real-time analysis plays a crucial role in accurate weather forecasting.
By incorporating tools from artificial intelligence and machine learning algorithms, it’s possible to significantly increase the reliability of weather forecasts. Weather models can be made much more accurate by using these tools not only to quickly process huge amounts of weather data but to offer a more refined approach the more the models are used.
Data Analysts who are trained to predict the weather offer many benefits to various stakeholders, from individuals to entire regions of a country. Weather Analysts rely on various data analytic and predictive analytic techniques in order to provide the most accurate and helpful forecasting models possible. Accurate weather predictions have many real-world ramifications; they can help people protect themselves, their products, and their belongings. By predicting what the weather will bring, lives can be saved.
Real-World Examples of Using Data Analytics for Weather Forecasting
Weather analytics plays a crucial role in many industries, from healthcare to agriculture to sports. The following are just a few of the many benefits of using data analytics for weather forecasting:
- Weather predictions help keep people informed about what to expect from the weather on a given day so they can plan accordingly for dressing as well as travel. It ensures that they can take necessary precautions to secure themselves, their loved ones, and their pets if an impending weather front poses any threats.
- Environmental factors affect human health in many ways. Variables such as humidity, temperature, air quality, and pollen counts are important considerations for many individuals who suffer from asthma, allergies, or wheezing. Predictive weather models can be applied to alert individuals of fluctuations in air quality or weather that could affect their overall health.
- Weather forecasting models are powerful tools that enable Data Analysts and Data Scientists to predict natural disasters, such as floods. In order to do so, data pertaining to variables such as an area’s rainfall in a given year or the surrounding road conditions are collected.
- The agricultural sector benefits from accurate weather predictions to help farmers decide when to plant, water, or harvest crops. Predictive analytics can also alert farmers about the likelihood of floods, at which time they may choose to harvest their crop, even if it has not yet fully matured.
- Forestry uses predictive weather analytics to anticipate, control, and ultimately prevent forest fires. In addition, this branch of analytics can be used to forecast the spread of harmful insects.
- Looking at weather forecasts helps to inform professional athletes and sports organizations about the conditions that may affect competition on a given day. They can then take necessary measures to change game schedules around severe weather or ensure that players are dressed appropriately for weather fronts.
- The weather plays a role in customers’ shopping patterns. Weather analytics can be applied to predicting car sales, which can fluctuate based on weather patterns.
- Major airlines rely on accurate weather predictions to cancel, delay, or reroute flights.
- Restaurants and food establishments use weather forecasts in several ways. By anticipating warm weather, they can take advantage of outdoor seating options, as well as anticipate larger crowds. In addition, when severe weather is forecasted, restaurants can put efforts into place to manage costs when fewer diners are expected.
- In addition to its effects on the restaurant industry, weather analytics also plays a role in food delivery services. Weather events such as icy roads, high temperatures, or torrential rain can affect food delivery options and delivery times. The weather can also affect the kinds of food and drinks customers order.
In the future, the field of weather analytics is expected to continue to play an important role in the way we travel, shop, and eat. The more we know about what to expect in terms of the weather, the more we can enjoy the sunny days and prepare for all else.
Start Learning Data Analytics with Hands-On Classes
Do you want to learn data analytics? If so, Noble Desktop’s data analytics classes are a great starting point. Noble offers live online data analytics courses in topics like Python, data analytics, and Excel, among others skills necessary for analyzing data. If you are interested in finding additional data analytics courses in your area, you can use Noble Desktop’s Classes Near Me tool.
Those who are committed to learning in an intensive educational environment may also consider enrolling in a bootcamp in data analytics or data science. These rigorous courses are taught by industry experts and provide timely instruction on how to work with data. Nearly 100 bootcamp options are available for beginners, intermediate, and advanced students looking to master skills and topics like data analytics, data visualizations, data science, and Python, among others.