Measuring the effect of an (online) advertising campaign based on a number of ratios such as for example reach, conversion, spontaneous or assisted name or brand awareness, click-through-rate (CTR) and cost per click (CPC). This contrasts with a regular request, or a more comprehensive, recurring reporting cycle. This is a data analysis technique that you perform on the basis of a one-off research question. Do you have questions or want more clarification or explanation? Contact one of our data coaches. In addition to the various types of data analysis, there are dozens of more specific data analysis techniques aimed at certain themes, disciplines or sectors. Low-threshold, standardized analyses, such as an analysis of visitor behavior in a store or on a website, can provide very interesting new insights. But small and medium-sized enterprises can also benefit from a solid data analysis. And accountants and controllers use statistical data analysis to detect large-scale (international) fraud. Governments use advanced data analysis to test whether their policies are effective. Automatic data analysis in aerospace plants and on oil platforms prevents costly downtime. Good data analysis can save product managers from marketing blunders. Organizations that analyze their customer data and/or perform sentiment analysis on social media have an edge. This model assumes a growth towards maturity when it comes to data analysis.įigure 3: Data Analysis broadly has four distinct stages in its growth to maturity Use data analysis as a competitive weapon One of the most well-known main classifications is Gartner’s growth model that broadly distinguishes four different types of data analysis (see figure): Talk to a data analyst Types of data analysisĭata analysis comes in all shapes and flavors. But how do you start doing advanced data analysis? First, we address the question: what types of data analysis exist? Machine data analysis does indeed take place automatically, but human judgment and common sense still play a role. However, people are questioning the increasing automation and an algorithm-driven society with numerous artificial intelligence applications. More and more people are realizing that data is the new gold that can provide valuable insights. Since the emergence of big data applications, however, the question “why data analysis” is no longer an issue.

So, when it comes to data analysis there is still a world to be won. Strangely enough, many decisions are still made on gut instinct. You will analyze your own business performance with an eye toward goal achievement, including monitoring types of Key Performance Indicators (KPIs). What is business analytics?īusiness analytics is particularly focused on gaining insights about specific business performance. Ideally, data analytics brings to light new trends, insights and patterns that significantly simplify business-critical decision making.Ī business analysis is both an externally and internally focused study of the state of affairs in an organization. Well-known data analytics tools include Tableau bi software, Google Analytics and Microsoft Power BI.įigure 2: Data Analytics is the umbrella for numerous applications and toolsĭata analytics is an umbrella term and uses the available data as raw material. In practice, the following terms are often used interchangeably:ĭata analytics is the broad field that uses dashboards tools as means to support decision-making processes in organizations. The data analysis process begins with a sharply defined research question.įigure 1: The five steps of Data Analysis displayed in a simplified mannerĭelineating the concept of data analysis is not so easy, because it lacks sharp definitions. Data analysis falls under the umbrella of data analytics and includes a number of sub-processes.ĭata analysis is the collection, cleansing, deduplication, integration and interpretation of data with the aim of arriving at a dataset that contains useful information for compiling a report or putting together a dashboard.

Basic data analytics techniques