EmPower Online, 29th May. Keboola Roadmap Reveal.
Don’t miss it!EmPower Online, 29th May. Keboola Roadmap Reveal.
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According to research giants, companies that rely on data analytics to drive business decision-making grow 2.5x faster than their lagging competitors.
Data analytics is invaluable to companies that want to drive growth.
Research from giants like McKinsey, the Financial Times, and Google confirms it: Companies that rely on data analytics to drive business decision-making grow 2.5x faster than their lagging competitors.
So how does descriptive analytics fit into the wider frame of data analytics?
Descriptive analytics is a branch of analytics that answers the business question: “What happened?”
It looks at current and historical data to understand what is happening in the business. For example, the above question could be translated into:
Usually, descriptive analytics is the foundation upon which all other analytic branches are built.
But with the advent of big data and exponential growth in the amounts of data modern enterprises hold in their data warehouses, new more advanced analytics techniques are developed.
With the use of machine learning and data mining algorithms, descriptive analytics is turning from a foundational technique to an advanced R & D approach to framing business decisions and business goals.
Data analytics is a wider area concerned with providing revenue-generating and de-risking insights. Data scientists or data analysts usually perform one of four types of analytics to answer different questions:
So if your data analysis is involved in determining what happened (descriptive analytics: How much revenue did we generate last quarter?), you will look at different data, then if you’d like to decide what future courses of action or optimizations you should take (prescriptive analytics: Should we sell more in the U.S.?), given the most likely future outcomes (predictive analytics: Revenue in the U.S. will grow faster than in other countries according to our regression analysis).
Descriptive analytics serves as a foundation for all other data analyses. It is employed in data science and business analytics as the first step before further analysis is conducted.
Let’s dive deeper into the practical applications of descriptive analytics.
Descriptive analytics reports on what happened, but not every report is part of descriptive analytics.
Let’s look at an example. Say your company made $1 million in revenue last year. Sounds like a lot, but what if I told you that that was the third year in a row where revenue dropped?
The role of descriptive analytics is to provide insights for decision-making and understanding of business performance.
This is why descriptive analytics is often used in business intelligence. By analyzing data, we can check how our performance is pacing against KPIs. For example, descriptive analytics can be used to report on how much revenue we made year-to-date and whether we hit our sales target.
Another use case of descriptive analytics is benchmarking. Setting up expectations of what is a good performance.
Concretely, the examples of descriptive analytics will vary by stakeholders:
How does descriptive analytics go about answering these questions?
There are three general areas of techniques used by descriptive analytics:
The success of descriptive analytics for driving insights is not only tied to the technique used but also to the overall process of performing analytics within your company.
For a descriptive analysis to be successful, you need to run through 4 necessary steps:
Building the end-to-end descriptive analytics pipeline can be time-consuming and expensive with limited engineering resources. Unless you can automate it.
Keboola can help you automate your descriptive analytics pipelines end-to-end.
Keboola is a data stack as a service platform that helps you integrate all your data tools and automate them.
Use it to build and deploy your analytic pipelines:
Try it out. Keboola offers a no-questions-asked, always-free tier, so you can play around and build your pipelines with a couple of clicks.
