![]() Analysis of customer survey data reveals that one primary motivator for customers to purchase the video game console is to gift it to their children. The customers, however, tend to be between the ages of 35 and 55. Taking the analysis a step further, this type includes comparing coexisting trends or movement, uncovering correlations between variables, and determining causal relationships where possible.Ĭontinuing the aforementioned example, you may dig into video game console users’ demographic data and find that they’re between the ages of eight and 18. Diagnostic Analyticsĭiagnostic analytics addresses the next logical question, “Why did this happen?” Here, descriptive analytics can tell you, “This video game console experiences an increase in sales in October, November, and early December each year.”ĭata visualization is a natural fit for communicating descriptive analysis because charts, graphs, and maps can show trends in data-as well as dips and spikes-in a clear, easily understandable way. It allows you to pull trends from raw data and succinctly describe what happened or is currently happening.ĭescriptive analytics answers the question, “What happened?”įor example, imagine you’re analyzing your company’s data and find there’s a seasonal surge in sales for one of your products: a video game console. Descriptive Analyticsĭescriptive analytics is the simplest type of analytics and the foundation the other types are built on. Here’s a breakdown of the types, which you can use individually or in tandem to maximally benefit from your company’s data.Ĭheck out our video on business analytics below, and subscribe to our YouTube channel for more explainer content! View VideoĤ Key Types of Data Analytics 1. To get the greatest insight from your data, familiarize yourself with the four key types of data analytics. ![]() Human resources and diversity, equity, and inclusion professionals, who gain insights into employees’ opinions, motivations, and behaviors and pair it with industry trend data to make meaningful changes within their organizations.Finance professionals, who use historical performance data and industry trends to forecast their companies’ financial trajectories.Product managers, who analyze market, industry, and user data to improve their companies’ products.Marketers, who utilize customer data, industry trends, and performance data from past campaigns to plan marketing strategies. ![]() Professionals who can benefit from data analytics skills include: If you formulate strategies and make decisions without considering the data you have access to, you could miss major opportunities or red flags that it communicates. Related: The Advantages of Data-Driven Decision-Making Who Needs Data Analytics?Īny business professional who makes decisions needs foundational data analytics knowledge. Writing algorithms is a more advanced data analytics skill, but you don’t need deep knowledge of coding and statistical modeling to experience the benefits of data-driven decision-making. These can help you examine data from different angles and create visualizations that illuminate the story you’re trying to tell.Īlgorithms and machine learning also fall into the data analytics field and can be used to gather, sort, and analyze data at a higher volume and faster pace than humans can. You can use tools, frameworks, and software to analyze data, such as Microsoft Excel and Power BI, Google Charts, Data Wrapper, Infogram, Tableau, and Zoho Analytics. When data analytics is used in business, it’s often called business analytics. DOWNLOAD NOWĭata analytics is the practice of examining data to answer questions, identify trends, and extract insights. How can you harness the power of data and experience these benefits at your company? Learning how to analyze data effectively can enable you to draw conclusions, predictions, and actionable insights to drive impactful decision-making.įree E-Book: A Beginner's Guide to Data & AnalyticsĪccess your free e-book today. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |