Today businesses have access to more data—to more types and more sources, internal and external—than ever before. The key to turning all this raw data into actionable insights is data analytics. Descriptive analytics, a foundational component of any business intelligence platform, is used to extract knowledge from an organization’s data stores, knowledge that can help firms better understand their business and their customers and make smarter decisions, whether in marketing, sales, or human resources. Through descriptive analytics, companies of all sizes and stripes can obtain the insights they need to boost efficiency, drive growth, enhance the customer experience, and gain an edge on the competition.

Descriptive analytics: Making sure decision makers have the information they need

The most basic form of business analytics, descriptive analytics is used frequently in the day-to-day operations of a business. It is used to measure company performance, ensure that targets are met, and inform management strategy. It helps keep everyone in an organization or department on the same page and provides decision makers with the information they need to do their jobs more effectively. Methods such as data aggregation, data visualization, and data mining are used to organize and visualize data and surface meaningful connections, patterns, and trends.

Business users employ descriptive analytics to create and share real-time dashboards, scoreboards, and reports, providing stakeholders with the metrics—be that financial, operational, or marketing KPIs—they need to make informed decisions about the performance, well-being, and direction of an organization. Descriptive analytics provide timely, actionable information to managers while encouraging fact-based decision making and helping increase transparency and productivity across the organization.

A user-friendly solution for descriptive analytics

Organizations that get the most value from descriptive analytics choose analytics tools that align with their business intelligence strategy and that easily foster adoption of analytics by users across their business. An easy-to-use yet powerful analytics platform like Qlik Sense enables users of all skill levels to explore, manipulate, and gather insights from data. Through an intuitive user interface, non-data scientists can load and combine data from multiple sources, use drag-and-drop functionality to build interactive dashboards and reports and share insights from descriptive analytics with decision makers and organizational stakeholders. And now with Qlik’s Insight Advisor, users can surface insights from data easier than ever before.

From descriptive analytics to prescriptive analytics: Taking analytics to the next level

Descriptive analytics is only the starting point of the analytics journey for forward-thinking organizations. In addition to descriptive analytics, there are three other types of analytics that can be leveraged in the enterprise:

• Diagnostic analytics, which is used to identify the cause of a problem or issue
• Predictive analytics, which is used to forecast trends or estimate the probability of future outcomes
• Prescriptive analytics, which is used to evaluate multiple what-if scenarios and determine the optimal course of action

Predictive and prescriptive analytics are considered more advanced types of analytics and typically require the support of data scientists and sophisticated analytics software leveraging machine-learning algorithms. By combining all four types of analytics, businesses can shift from being data-informed to insights-driven. They can streamline operations, accelerate problem-solving, and improve the quality of decision making and planning across the organization.

A robust platform for every analytics use case

With Qlik Sense, your organization doesn’t have to stop at descriptive analytics. Qlik’s robust toolset can help you take analytics to the next level. Providing you with industry-leading analytics capabilities, Qlik Sense lets you tackle even the most complex analytics challenges. Featuring unmatched analytical power, sophisticated AI, and a scalable multi-cloud architecture, Qlik’s enterprise analytics platform gives you the power, scalability, and cutting-edge technology you need to unlock the possibilities and real value in your data.

Qlik Sense empowers everyone in your organization to access, analyze, and take action with data. Qlik’s one-of-a-kind Associative Engine brings together information from all your data sources, indexing and understanding all relationships that it finds. Users aren’t limited to predefined queries or pre-aggregated data, so they can probe for answers and insights in any direction they choose to pursue. And with AI under the hood, Qlik Sense can even auto-generate charts and visual insights based on the user’s search criteria and selections. Intelligent data preparation, smart visualizations, and context-aware insight suggestions accelerate time to insight, exposing hidden relationships, patterns, and trends users might otherwise miss. With Qlik Sense, users are guided in new directions, helping them build confidence while learning how to lead with data.

FAQs

What is the purpose of descriptive analytics?

It is used by organizations to evaluate and track the performance of various teams or departments within a company or the performance and efficiency of an entire firm. Descriptive analytics provides managers and other organizational stakeholders with the timely information they need to ensure that targets are met, identify areas in need of improvement, and make fact-based decisions.

What is the difference between descriptive and prescriptive analytics?

Descriptive analytics is primarily focused on the recent past while prescriptive analytics is focused on the future. Prescriptive analytics is also more difficult to implement, requiring large amounts of high-quality data, the support of data scientists, and sophisticated analytics tools leveraging machine learning algorithms and feedback systems.

What are the four types of analytics?

In order from the most basic to the most advanced, the four types of analytics are descriptive, diagnostic, predictive, and prescriptive. Descriptive analytics is used to describe what happened while diagnostic analytics is used to understand why something happened. Predictive analytics is used to forecast what is likely to happen while prescriptive analytics is used to recommend a course of action.