Due to the sheer amount of data now accessible to companies, it is easier than ever to leverage information accumulated in order to push real business value. Nevertheless, it can be tricky to find the best way to examine the data.
Hence, why you need to understand the types of data analytics
There are four different types of data analytics.
Descriptive analytics
Descriptive analytics helps to better comprehend the changes that have ensued in a business. It organizes raw data from several data sources to give significant insights into the past. With a scope of data, decision-makers get a full view of performance and trends from which they can base their business strategy off of.
The statistical technique used within this type of analysis usually focuses on the patterns in data which help to filter out less meaningful data. Descriptive analytics provides significant information in an easy-to-understand structure.
Diagnostic analytics
Diagnostic analytics measures data against other data to answer the question of why something happened. This occurs by taking a deeper look at data in a bid to grasp the causes of events and behaviours. It lets you understand your data faster to solve vital questions. Diagnostic analytics reveal the rationale behind specific results.
With this type of analytics, you get in-depth insights into a specific problem by interpreting your complicated data into visualizations and insights that everyone can understand. And you should have detailed information at your disposal, else, data collection may turn out to be time-consuming.
Predictive analytics
Predictive analytics predicts future trends. Using the findings of descriptive and diagnostic analytics, predictive analytics can detect clusters and exceptions, and identify risks and opportunities for the future. It is a valuable tool for forecasting.
Predictive analytics permit organizations to become proactive, forward-looking, foresee outcomes and behaviours based upon the data and not on assumptions. Keep in mind that the accuracy of the results highly depends on data quality and stability of the situation since forecasting is just an estimate.
Prescriptive analytics
The objective of prescriptive analytics is to assist your business in identifying data-driven strategic decisions and eliminate a future problem. Prescriptive analytics uses data to comprehensively understand and predict what could happen, then advises the best steps forward based on informed models.
Advanced tools and technologies, like machine learning, business rules, and algorithms are utilized to stimulate various approaches to numerous outcomes. Prescriptive analytics also helps to reduce errors because it involves data aggregation, both internal data and external information.
So what’s next?
Now that you understand the different types of data analytics, let’s talk about how to identify the one(s) your business needs. First, you need to provide answers to the following questions:
Firstly, what is the present state of data analytics in your business?
Secondly, what is the depth of the data needed?
Thirdly, how far are your present data insights from the insights you need?
Finally, are there obvious answers to the issue?
The answers will guide you on the next steps and strategy. You will be able to work with the best data analytics option with the most favorable technology stack, and then commence and execute it effectively. Keep in mind that the more complex an analysis is, the more value it brings.
The goal of any analytics program should be more relevant information, which will lead to more valuable decisions and a more complete understanding of your business landscape. Additionally, if you want to read about our Custom Software Solutions and Consulting Services, Get In Touch and we will get back to you shortly.
