Choosing Your First Data-Analytics Project

If you are new to data analytics, you may be wondering where to begin.

Predictive analytics forecasts what might happen in the future.

Every organization has critical data. It could pertain to customers, products, projects, or even processes. Data analytics analyzes this data to create value and actionable insight. Analytics is a positive force that is transforming organizations around the globe. It helps cure diseases, grow businesses, serve customers better and improve operational efficiency.

If your organization is new to data analytics, our next series of blog posts can help you understand how to get started utilizing data analytics to help your organization achieve its goals. Before you begin implementing anything, it is important to understand the three basic types of data analytics: descriptive, predictive and prescriptive.

Descriptive Analytics

Descriptive analytics help an organization understand the story told by its data. It provides insight into what has happened in the past. Visualization is a powerful tool in descriptive analytics. It can help expose information that might otherwise be lost. It can also allow the viewer to comprehend information contained in large data sets. One common example of descriptive analytics is when sales organizations want to look at sales by customer, by territory, by region and by market. This type of information rendered in a table or chart is used in many sales teams to understand the sales pipeline. Most management reporting, such as sales, marketing, operations, and finance, is considered descriptive analytics.

Predictive Analytics

Predictive analytics forecasts what might happen in the future. Many companies study customer behavior in an attempt to predict which customers are most likely to buy products or services. For example, a sequence of visits on a web site might indicate a likelihood of a purchase. Predictive analytics derives these forecasts from existing data using a model or algorithm.

Prescriptive Analytics

Prescriptive analytics seek to assist decision makers in choosing the best course of action for a given situation. It sometimes utilizes predictive analytics and adds a recommended course of action. Our example sales organization might ask: should we hire more direct sales people or partner with a third party distributor? Analytics might illustrate the success and productivity of existing sales people and distributors to guide this decision.

Choosing Your First Analytics Project

The simplest type of analytics is descriptive. Thus, it is a good choice for a first project. A descriptive analytics project for a restaurant chain might seek to generate reports that shed light on the following questions:

  • What is the top performing entrée?
  • Which are the top ten performing restaurants by sales?
  • Which are the top ten by revenue?
  • Which are the bottom ten?
  • What is the rate of employee turnover?
  • What is the best performing menu item?
  • What is the most profitable menu item?
  • Which menu items have the most margin?

Arming the restaurant chain with this type of information provides them with insight that could influence their investment in new menu items or new locations. This could help them grow their top line or increase efficiency by focusing on the most profitable offerings. With data analytics being more and more utilized across the globe, it is hard to imagine companies being able to compete in the 21st century without these insights.

You may be ready to charge ahead and start your first data analytics project, but before you do, give some thought to your processes, tools and methodologies. We’ll cover these critical topics in future blogs.

DataKitchen is leading the DataOps movement to incorporate Agile Software Development, DevOps, and manufacturing-based statistical process control into analytics and data management. We provide the world’s first DataOps platform for data-driven enterprises, enabling them to support data analytics that can be quickly and robustly adapted to meet evolving requirements.