You know which are the best data analysis techniques for decision making that a manager can use?
That's the question one of my prospects asked me the other day.
The truth is that it was frozen. Almost not knowing what to say to him. I am not a statistician and the little I remember about this discipline is what I learned during my university studies at Deusto in 1975.
Come on, there's an eternity in the last century!
The truth is that I got out of this question as best I could.
And for a few days, I guessed a viable answer. So, after some research and internal questions to my team, I decided to write this post on data analysis techniques that all managers should at least know.
(* 13 *) List of useful data analysis techniques for your business
Commercial promotion. I will not go into the possible tools to perform these analyzes in this post. I reserve this for other posts on this blog.
Having said that, I am going to list these data analysis techniques that can help your decision-making process in your organization:
1 .- # Correlation analysis
It is a technique of statistical data analysis. It is used to establish whether there is a link between two different quantitative variables. and how strong is this link between the variables. In general, it is used when it is suspected that two variables follow or have an equivalent evolution. Ex: the IBEX 35 index and the DAXX. You can find more here Correlation analysis Yes here.
2.- # Regression analysis
This is another of the statistical data analysis techniques to study the link between different variables. It is used when it is suspected that one of the variables may affect (independent variable) the behavior of the other (dependent variable) or others. You can get more information about regression analysis here Yes here.
3 .- # Data visualization
the Data visualization It is by far one of the most requested and appreciated data analysis techniques today due to the ease with which it is easy through a graph or an image to detect patterns in the data. It is fundamentally useful when we seek to understand large volumes of data in a fast and easy way. Infographics and charts are the most popular form of these types of techniques. using software like Tableu Boureu or Qlick View
4 .- # Scenario analysis
Scenario analysis is about analyze a range of future events with alternative results. It is good to use it when we are not sure of the decision to make or the way forward. It's good scenario analysis example
5.- # Data Mining
Data mining or data processing is a data analysis procedure designed to work with large volumes of data. It is now better known as Big data and is used to detect patterns, relationships or relevant information that can improve the performance of customer operations and the Internet of Things.
6.- # Sentiment analysis
This is another of the data analysis techniques that became very popular thanks to social media. Try to establish the attitude of an individual or a group towards a particular issue. It is used to try to understand the opinions of the different agents that interact in an industry. The great difficulty of this type of analysis is that based on subjective aspects very difficult to measure that have to do with human emotions.
7.- # Semantic analysis of texts
This type of analysis, also called text mining, is a procedure that tries to extract value through semantic analysis large volumes of texts. Linked to the state of the art, it seeks that PCs are able to understand what they are indexing and get data from unstructured texts. The tool I know best for this type of analysis is BItext.
8.- # Analysis of patents and scientific literature
This data analysis technique uses metadata from scientific publications and patents to extract information on trends and relationships between studies, authors or intellectual property. It is one of the most used techniques in monitoring technological trends.
9.- # Monte Carlo Simulation
This mathematical probability technique is used to measure the approximate risk of a certain event occurring. It is very useful to understand the implications that a certain course of action derived from a decision can have.
10.- # Programming and mathematical optimization
Also known as linear optimization, is a method to identify which is the best viable result given certain specific restrictions of our situation. It is widely used to solve certain problems in production processes and establish how to minimize costs or maximize profits.
11.- # Mathematical prediction
It is a compilation of statistical techniques that uses time series data to predict the most likely outcome that may occur in the near future. The foundation of these data analysis techniques is looking at what happened in the past to find out what will happen in the future. It is widely used in macroeconomic projections.
12.- # Neural Networks
It is perhaps one of the most complex data analysis techniques available. the Neural networks They try to simulate the decision and information process of the brain or groups of neurons. The objective of these networks is to simulate the learning procedure of a human brain in a computer to facilitate the decision making in artificial intelligences.
13.- # AB experiences
Also known as AB Test or split test It is one of the most used techniques in digital marketing to check the user's reaction to a publication and see which one works best. It is primarily used to test hypotheses when launching a new product, advertising campaign, or message in an advertisement.
Other data analysis techniques on the rise
In conclusion this article and do not delay too much on this topic. I think it is necessary to mention at least a few other data analysis techniques that are on the rise:
- Image analysis: It is a procedure for the extraction of information through images such as photographs, medical images and graphics. It is used in the healthcare industry for disease detection and in the security industry for face detection.
- Video analysis: equivalent to the previous one, it also tries to recognize and predict a person's behavior.
- Voice analysis: It is a procedure for extracting information by audio to facilitate understanding of conversations. This can be used to analyze telephone conversations in a call center.
Image, voice and video analysis are tools that large companies use to make the most of their processes. Even when they are far from the general public.
Recommended reading on data analysis
For more information on data analysis techniques, see the following manuals:
Decidedly, not everything in the world of data analysis is, but it's a good start, I assure you.
I look forward to this compilation entry from data analysis techniques It has been a great help to you. If you know of an additional manual that I did not mention, you can tell about it in the comments.
