What is Time Series Analysis?
Time plays an integral role in the field of data analytics. Time series analysis is one of the most common types of data analysis. It is a statistical technique focused on analyzing trends or events that happen in a time series or particular interval. When performing time series analysis, instead of recording random or intermittent data points, a Data Analyst records points of data that occur at regular intervals spread over a period of time. This valuable tool provides insights into how variables can change over time.
In order to successfully execute time series analysis, it’s important to work with a large set of data points for a representative sample size. This leads to more reliable and consistent results and helps guarantee that the patterns or trends that are discovered aren’t just outliers. In this form of analytics, time can serve as an independent variable used to make forecasts about the future. In addition, the data that’s collected can draw from past historical data to shed insights on what may still occur.
There are several different characteristics of time series that can be modeled to make accurate predictions:
- Autocorrelation pertains to the similarities between observations as a function of the gap of time between them.
- Seasonality is the term for periodic fluctuations, such as how energy consumption may be higher during the day than at night, or how online sales tend to go up before the holidays.
- Stationarity pertains to when a time series’ statistical properties remain constant over time. Stationary time series are the most desired for modeling; those that aren’t stationary often must be transformed so that they are stationary.
How is Time Series Analysis used in Data Analytics?
Time series analysis has been used in various forms for thousands of years. This field of data analytics can be traced back to the ancients, who used it to record the movement of planets, as well as to navigate uncharted parts of the world. Today, time series analysis remains a valuable tool when working with non-stationary data, such as elements that regularly fluctuate or change over time. Various industries, like retail, economics, and meteorology, all draw from time series analysis to help understand variables that change in time.
The field of time series analysis has many applications across industries. A time series may experience upward or downward trends, or might only fluctuate slightly around a central mean, such as the body temperature in humans. Some time series pertain to single cycles, like daily blood pressure readings, or deal with a variety of cycles, such as daily and yearly outdoor temperature patterns. Data Analysts who are trained to work with time series analysis provide valuable insights that help humans live healthier, safer, more productive lives.
Here are some of the most common industry uses of time series analysis:
- Time series analysis is a valuable tool for measuring societal trends like birth rate over time, migrational data, population, or political movements.
- When applied to the financial sector, time series analysis can measure stock prices, interest rates, quarterly sales, and automated stock trading.
- In the health sector, time series analysis can be applied to heart rate (EKG), blood pressure, brain activity (EEG), and cholesterol.
- When working with the environment, time series analysis helps to keep track of temperature fluctuations, rainfall and precipitation, weather fronts, cloud cover, humidity, air pollution, and global temperatures.
Real-World Applications of Tableau Time Series Analysis
Tableau offers many features to help with the time series analysis process. Its drag-and-drop feature can be used to study times based on the day of the week. In addition, time comparisons such as Year-Over-Year growth and Moving Averages can also be computed in this manner. Tableau also makes it possible to join separate data sources into one graph, a helpful feature for streamlining insights into one location.
The following are several real-world examples of how time series analysis in Tableau is being used by organizations around the world to help improve operations, reduce operational costs, and lead to better overall customer experience:
- Stamford Health turned to Tableau time series analysis for help with inefficient resource allocation, as well as inflated care costs. They gathered historical data pertaining to treatments, how long patients spent in the hospital, and various conditions, in addition to other variables. Stamford Health used this information to spot ideal times when medicine could be administered, which ultimately led to a reduction in patients’ length of stay. Measures such as these not only reduced costs for the patient, but for the hospital too.
- Prior to working with Tableau time series analysis, Bronto Skylift had been struggling with inaccurate sales forecasting, as well as time-intensive operations and manufacturing practices. These practices were affecting their sales. In order to improve operations, they leveraged Tableau to reduce the time required to analyze data from a full day to just an hour. By applying time series analysis in Tableau, as well as forecasting modeling, Bronto Skylift could successfully anticipate supply chain and processes in the manufacturing department and even account for variations in trends due to seasonal changes. They ultimately were able to have more accurate, affordable labor, inventory, and equipment.
- Exelon applied Tableau time series analysis in order to find a way to handle time-consuming audits that ultimately weren’t helping their business grow. Typically, Exelon’s auditing process involved interviewing administrators and transcribing records of the auditing process. With the help of Tableau, Exelon was able to review a full year’s worth of data and discover trends that may have not been otherwise uncovered on their first round of review.
- In Des Moines, Iowa, public schools worked with Tableau time series analysis to study five years of student achievement data. Educators used the information gathered from this study to help spot at-risk learners, as well as to monitor their progress over time.
- The Texas Rangers make game-day decisions using Tableau time series analysis. The team’s front office combined all data from each available source to make sure that a complete view of the data was available. With the help of advanced dashboards, the marketing and sales teams applied time series analysis in Tableau to locate promising opportunities to forecast against season trends. The Texas Rangers even applied time series analysis to a game with lower-than-expected ticket sales in order to boost attendance. They offered a promotional offer for Father’s Day to increase ticket sales.
As the above list indicates, those using Tableau for time series analysis can provide their business with helpful, pragmatic solutions to problems such as revenue allocation, data analysis, and time-intensive operations. This is why thousands of companies and organizations use Tableau for their data analytic and visualization needs.
Hands-On Data Analytics & Tableau Classes
If you’re interested in learning more about time series analysis, as well as the other methods for analyzing and visualizing data, Noble Desktop has you covered. Their data analytics classes are offered in New York City, as well as in the live online format in topics like Python, Excel, and SQL. In addition, more than 130 live online data analytics courses are also available from top providers. Topics offered include FinTech, Excel for Business, and Tableau, among others. Courses range from three hours to nine months and cost from $219 to $60,229.
For those searching for a data analytics class nearby, Noble’s Data Analytics Classes Near Me tool provides an easy way to locate and browse approximately 400 data analytics classes currently offered in the in-person and live online formats. Course lengths vary from three hours to nine months and cost $119-$60,229.
Those who are interested in finding nearby Tableau classes can use Noble’s Tableau Classes Near Me tool. This handy tool provides an easy way to locate and browse more than three dozen of the best Tableau classes currently offered in the in-person and live online formats so that all interested learners can find the course that works best for them.