There are mainly two ways through which you make decisions that are, we either follow our instincts or simply use the Data Analytics approach to fix things and decide.
Choosing the latter approach means being well informed about the types of Data Analytics. If you choose the former, you must read on to find out more about Data Analytics so that you can use the right ones in the future.
It is important to know how much an individual needs to analyze the data for insights.
Data Analytics And Its Types
Data Analytics consists of both complex and simple types of Data Analytics. They are known as Descriptive Analytics Diagnostic Analytics, Predictive Analytics, and Prescriptive Analytics.
Descriptive Analytics – Determining ‘What Happened’?
Descriptive Analytics is a process that informs about the changes which have already taken place in the past in a business.
- It focuses on basic right and wrong and doesn’t delve into the existing reasons behind that right or wrong.
- It lets a business decide which strategies to enforce in the future based on past performances.
- It diagnoses the strong as well as weak points of any organization or company.
- Solely Descriptive Analytics must not be used by those companies which are essentially dependent on data. It is recommended that such companies figure out other types of Data Analytics.
- The metrics can be drawn out giving a distinct comparison with past performances.
- Examples of this type of Data Analytics include KPIs about sales growth, revenue generated per customer, marketing campaigns, Social Media analysis, survey results, etc.
Diagnostic Analytics: Answering ‘Why It Happened’?
Diagnostic Analytics uses a variety of tools such as data mining, drill-down, data discovery, and correlations to depict the reason behind the changes in a business.
- It analyses an existing current specific issue in detail.
- It provides the main reason behind the trend.
- It can be done manually.
- Example: You might wonder why there was a sudden and drastic increase in sales at a specific time or let’s say why the click rate was really low at a given time. With the help of Diagnostic tools, you’ll be able to find answers to such questions.
Predictive Analytics: Answering ‘What Next’?
As the name suggests, Predictive Analytics is used to predict or forecast the trends likely to rule in the future. This prediction is based on previously available records.
- Predictive Analytics can be used to predict the weather, convert voice messages to text, and create video games and portfolios on investment.
- It provides an opportunity for businessmen and investors to take complete advantage of the available resources and reduce risk.
- Tools ranging from AI Artificial Intelligence to Machine Learning, from Data Mining to Statistics, all of these help determine the possible outcome in the future.
Prescriptive Analytics: Answering ‘Which Action’ must be taken?
Prescriptive Analytics determines the kind of action that needs to be taken to avoid any future risk and also to utilize to the fullest the current trends.
- It helps in identifying opportunities based on the repetitive purchasing behavior of the customers through the sales history and customer analytics.
- Prescriptive Analytics helps in gaining in-depth insight into various outcomes and provides all the factors responsible for decision making.
- A company or organization can also get to know about the uncertainty involved along with the possible negative probabilities associated with them.
- This leads the companies and organizations to pre-plan imagining the worst possible outcomes.
- Examples: Healthcare organizations and Financial Sectors can utilize Prescriptive Analytics.
Choosing a suitable Data Analytics type
Different surveys for Data Analytics were conducted for the period 2016 to 2019.
- According to the ‘Global Data & Analytics Survey- Big Decisions’ in 2016, 2000 company executives were asked to describe their company’s decision making, which is as follows:
- Descriptive Analytics- 58% (appeared under the category of ‘rarely data-driven)
- Diagnostic Analytics- 34 % (appeared under the category of ‘somewhat data-driven)
- Predictive Analytics- 36 % (appeared under the category of ‘Highly data-driven)
- In another survey in 2017, the importance of advanced analytics was highlighted by 2,800 company executives.
- As per the Advanced & Predictive Analytics Market Research in 2018, advanced analytics was marked as crucial for the first time.
- In 2019, yet another report claimed advanced analytics is highly important as per the trends of Business Intelligence.
Appropriate Data Analytics for Business Goals
To understand exactly what type of Data Analytics will suit your organization you must determine the following key points:
- The status of Data Analytics in your company currently.
- The intensity of analyzing the data and checking whether the existing issues are easily solvable or not.
- The intensity of the gap between the available data insights and the data insights required in the future.
Conclusion
- For enhanced ROI, you will require experts who are experienced in providing Data Analytics.
- Design the best and most effective strategies for Data Analytics.
- The right Data Analytics provider will analyze your company’s current data analytics stats and also share valuable tips for better technical solutions with the right blend of Data Analytics.
- Try and avoid specialized professionals in Data Analytics as they will prove to be highly expensive and the process will turn out to be lengthy.
