2.6 Data Analysis

2. Technological Trends

2.6 Data Analysis

INTRODUCTION

Hello Everyone

In this presentation we are going to talk about data analysis, as we all know the use of data is extremely important for companies to know their held and to take decisions, as well as for technology, especially artificial intelligence and machine learning. So in this presentation we are going to talk about what data analysis and mining is; and some of its tools, how to analyze data and how this relates to technology.

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DATA ANALYSIS INTRODUCTION

Nowadays, data analysis has become a fundamental tool for decision-making in companies. It is a discipline that allows you to analyze large amounts of information and extract valuable knowledge to improve the performance of companies. For example, manufacturing companies often record the run time, idle time, and work queue of various machines, then analyze those to better plan workloads and keep machines running closer to their maximum capacity.

WHAT IS DATA ANALYSIS

Data analysis is the process of examining, cleaning, transforming, and modeling data with the goal of discovering useful information, reaching conclusions and supporting decision-making. This process involves the application of various techniques and methods to extract meaningful patterns, trends, correlations, and insights from data sets. The information obtained can be used to optimize processes and increase the overall efficiency of a business or system. “It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts,” Sherlock Holmes proclaims in Sir Arthur Conan Doyle's A Scandal in Bohemia.

WHAT IS DATA ANALYSIS

DATA ANALYSIS TYPES

There are several different types of data analysis. These are the following:

Descriptive

Diagnostic

Prescriptive

Predictive

DATA ANALYSIS PROCESS

As the data available to companies continues to grow both in amount and complexity, so too does the need for an effective and efficient process by which to harness the value of that data. The data analysis process typically moves through several iterative phases. Let’s take a closer look at each.

• Identify the business question you’d like to answer. What problem is the company trying to solve? What do you need to measure, and how will you measure it?

• Collect the raw data sets you’ll need to help you answer the identified question. Data collection might come from internal sources, like a company’s client relationship management (CRM) software, or from secondary sources, like government records or social media application programming interfaces (APIs).

• Clean the data to prepare it for analysis. This often involves purging duplicate and anomalous data, reconciling inconsistencies, standardizing data structure and format, and dealing with white spaces and other syntax errors.

DATA ANALYSIS PROCESS

• Analyze the data. By manipulating the data using various data analysis techniques and tools, you can begin to find trends, correlations, outliers, and variations that tell a story. During this stage, you might use data mining to discover patterns within databases or data visualization software to help transform data into an easy-to-understand graphical format.

• Interpret the results of your analysis to see how well the data answered your original question. What recommendations can you make based on the data? What are the limitations to your conclusions?

Name: Master Data Analysis on Excel in Just 10 Minutes Duration: 11:31 Account: Kenji Explains

DATA ANALYSIS PROCESS IN EXCEL

DATA ANALYSIS (DATA MINING)

Now that we know about Data Analysis, we need to incorporate another definition when searching to take advantage of the information, Data Mining. Data mining is the process of searching and analyzing a large batch of raw data in order to identify patterns and extract useful information. The difference of Data Analysis and Data Mining is that Data Analysis will help to clean the information and present it on a way that will be easy to take decisions as for Data Mining the information will be worked to extract specific information.

DATA ANALYSIS (DATA MINING)

Data mining involves exploring and analyzing large blocks of information to glean meaningful patterns and trends. The data mining process breaks down into four steps:

1. Data is collected and loaded into data warehouses on site or on a cloud service.
2. Business analysts, management teams, and information technology professionals access the data and determine how they want to organize it.
3. Custom application software sorts and organizes the data.
4. The end user presents the data in an easy-to-share format, such as a graph or table.

DATA ANALYSIS (Data Mining Techniques)

Data mining uses algorithms and various other techniques to convert large collections of data into useful output.

Association rules

Classification

Decision trees

Clustering

K-Nearest Neighbor

Neural networks

DATA ANALYSIS (Data Mining Techniques)

Predictive analysis

Name: What is Data Mining Duration: 06:52 Account: IBM Technology

DATA ANALYSIS (DATA MINING)

DATA ANALYSIS (DATA MINING - DECISION TREES)

A decision tree is a non-parametric supervised learning algorithm, which is utilized for both classification and regression tasks. It has a hierarchical, tree structure, which consists of a root node, branches, internal nodes and leaf nodes. As you can see from the diagram, a decision tree starts with a root node, which does not have any incoming branches. The outgoing branches from the root node then feed into the internal nodes, also known as decision nodes. Based on the available features, both node types conduct evaluations to form homogenous subsets, which are denoted by leaf nodes, or terminal nodes. The leaf nodes represent all the possible outcomes within the dataset.

DATA ANALYSIS (DATA MINING - DECISION TREES)

As an example, let’s imagine that you were trying to assess whether or not you should go surf, you may use the following decision rules to make a choice:

DATA ANALYSIS (DATA MINING - DECISION TREES)

An example in a business would be something like, "earnings are expected to increase by $5 million.” But since the events indicated by end nodes are speculative in nature, chance nodes also specify the probability of a specific projection coming to fruition.

Name: How To create a Decision Tree Duration: 05:31 Account: Wondershare Edraw

DATA ANALYSIS (DATA MINING - DECISION TREES)

QUESTION?

WHY IS DATA ANALYSIS AND DATA MINING IMPORTANT IN A BUSINESS ?

CONCLUSION

In conclusion, we can say that information is one of the most important resources that a company can have since it helps to know the health of a company and to make informed decisions. Every day companies generate a greater amount of information (Big Data) and there are processes such as data analysis and data mining that help clean and process the information so that it is something useful. Apart from all this, the work of information is essential for technology, specially for artificial intelligence (we will see this in another presentation)

BIBLIOGRAPHY CONSULTED

• Coursera Staff, (Nov,2023) What is data analysis https://www.coursera.org/articles/what-is-data-analysis-with-examples

• Data Discovery Solutions, (Mar, 2023) La Importancia del Análisis de Datos https://es.linkedin.com/pulse/la-importancia-del-an%C3%A1lisis-de-datos-data-discovery-solutions

• Alteryx, (-) Qué es Análisis de datos https://www.alteryx.com/es/glossary/data-analytics#:~:text=El%20an%C3%A1lisis%20de%20datos%20es,respaldar%20la%20toma%20de%20decisiones.

• Arthur Pinkasovitch, (May, 2024) Using Decision Trees in Finance https://www.investopedia.com/articles/financial-theory/11/decisions-trees-finance.asp

• Alexandra twin, (Feb, 2024) What Is Data Mining? How It Works, Benefits, Techniques, and Examples https://www.investopedia.com/terms/d/datamining.asp

• IBM, (-) What is a decision tree https://www.ibm.com/topics/decision-trees#:~:text=A%20decision%20tree%20is%20a,internal%20nodes%20and%20leaf%20nodes.

Todos los recursos educativos abiertos, elaborados por la Universidad Anáhuac México y su equipo de docentes, se proveen bajo la licencia Creative Commons Reconocimiento -NoComercial- SinObraDerivada CC BY-NC-ND. http://creativecommons.org/licenses/by-nc-nd/4.0/

Both Data Analysis and Data Mining help us to have useful information in order to take good decisions. Also, Both are basic principles for Artificial Intelligence and Machine Learning, we will be covering this on another presentation.