Descriptive Analytics: The Starting Point of Business Intelligence
Sr. Content Marketing Manager, Sigma
Today’s organizations are generating vast amounts of data in CRMs, ERPs, SaaS platforms, and more. But data must be interpreted to be of value. Descriptive analytics is where business intelligence begins, providing a clear picture of what has happened in the past. With this accurate understanding of trends and performance, teams are prepared to explore ways to take advantage of opportunities and find solutions to problems.
What is Descriptive Analytics?
Descriptive analytics is the starting point of business intelligence. It answers questions related to trends and business performance. Using data aggregation and data mining, descriptive analytics initiatives result in reports, dashboards, and/or visualizations such as line graphs, bar charts. The stories told in these data charts reveal a clear picture of what has happened in the past. Once a business team has a strong understanding of what has happened, they can use additional analytic methods, including predictive and diagnostic analytics to predict future outcomes, make interpretations, or advise on future actions.
How Does Descriptive Analytics Work?
The descriptive analytics process typically starts with identifying benchmarks for performance in a given business area (sales, finance, operations, etc.). With these KPIs in place, you’ll then determine what data sets are needed to inform the analysis and where to source them.
After preparing the relevant data sets, you’ll use various methods to spot trends and measure performance, including pattern tracking, clustering, summary statistics, and regression analysis. Finally, you’ll create visualizations to make the data quickly and easily understandable. Thanks to tools like Sigma, even non-technical decision-makers can do this type of analysis — without SQL or other coding skills.
What Can Descriptive Analytics Reveal?
Descriptive analytics can answer a variety of business questions. Specifically, it excels in the following areas:
Historical trends — Trend analysis can reveal opportunities developing in the market or issues that are becoming more significant. It can also track trends that can be used to inform strategy. For example, a retailer may track sales for a specific SKU over the course of the year and find that demand skyrocketed unexpectedly in an off-season month.
Business performance — Descriptive analytics also reveals insights into business performance metrics across every department in the business. Organizations can identify opportunities for improvement in individual performance, team performance, and overall company performance. For example, a business may discover that a customer service team for a particular product portfolio is experiencing greater churn than the rest of the teams.
Examples of Descriptive Analytics in Action
Let’s look at several ways organizational departments are using descriptive analytics, including the types of reports, dashboards, and visualizations they’re generating.
Sales teams — A sales team may identify which customer segments generated the highest dollar amount in sales last year, developing a report with recommendations for the C-level leadership team.
Marketing teams — A marketing team may uncover which social media platforms delivered the best return on advertising investment during the last quarter, creating a live dashboard that updates automatically each month with fresh data.
Finance teams — A finance team may track month-over-month and year-over-year revenue growth or decline by product category, developing colorized line graphs that show which categories should be explored further.
Operations teams — An operations team may track raw material deliveries and inventory, creating a bar chart that reveals where opportunities exist for streamlining just-in-time inventory strategies.
Descriptive Analytics with Sigma
Descriptive analytics is an important first step in business intelligence. Business teams must have a thorough and accurate understanding of historical trends and performance before they can begin to look for opportunities or solutions to problems. Without this insight, any action taken may be misdirected.
Traditional BI tools simply weren’t built to make it easy for line of business teams to explore data in this way. But Sigma was purpose-built to empower teams across finance, sales, marketing, and more to independently investigate live data at scale, easily find answers to ad hoc questions, and work together to get to the heart of complex problems in real-time. Here’s how Sigma is supporting teams who want the ability to explore data on their own.
Direct connection to a centralized data source
Sigma connects directly to a company’s cloud data platform, a centralized repository that automatically collects and stores data. This means that the data underpinning dashboards is always live, ensuring that data is always up-to-date and can be relied upon for accuracy. And because data is never extracted to a spreadsheet, sensitive information and corporate plans are kept safe, secure, and governed.
Intuitive interface and simple collaboration
Sigma’s intuitive user experience and flexibility of analysis empower cross-functional team members to do productive, free-flowing analysis. Sigma also allows multiple scenarios to be organized and annotated within a single online doc for a collaborative, Google Docs-like experience.
Speed for faster insights
The speed and concurrency of Sigma’s direct connection to a cloud data platform mean that users have a snappy, responsive experience no matter how large and complex the datasets and models are or the number of users collaborating together.
Start Leveling Up Your Performance with Descriptive Analytics
Descriptive analytics enables teams to find the information they need for effective decision-making. A self-service business intelligence tool like Sigma empowers decision-makers to conduct their own analyses, resulting in more data-driven decisions across the organization while maintaining compliance.