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It is the process of checking the raw data that is using statistical and logical techniques. Data Analysis is used to understand data and analyze it according to the need. In data analysis, we collect and display data in a table, bar chart, line graph, etc.
It is a significant component of Data Mining and Business Intelligence. Data analysis involves processes like drawing graphs and charts to illustrate data, and it takes into consideration both dependent independent variables in research. Data analysis is applicable in many areas such as corporate business, social science, and applied science, etc.
Data mining is a process to turn raw data into useful information, and it is a process of extracting hidden predictive information from the database. A person in a business can learn more about their client’s behavior by using the software, and it can help develop marketing strategies and increase sales and decrease costs.
Data integration is the combination of technical and business processes. It is used to combine data from different sources, and it maintains essential and valuable information. Most companies often need to move application data from one source to another source. The implementation of data integration is building an organization's data warehouse.
It is the process of presenting data in a graphical format and figures. In companies, data visualization is used to see and understand trends and outliers in data. Many companies use data visualization software to track their initiative.
Data modeling is a process used to describe and analyze data requirements. In other words, we can say that it is a set of tools and techniques used to understand and analyze data. Data modeling defines how a company should collect, update, and store data.
A data modeler can create an entity-relationship diagram to visualize the relationships between fundamental business concepts. It can also create a data map to resolve potential data issues for data migration.
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Data mining is the process of getting data from different sources. In other words, it is the way to discover the patterns from the large data sets. It used various methods, i.e., related to statistics, machine learning, and database.
A data warehouse is the collection of massive amounts of information in the form of a central repository. Data scientists and data engineers use it to make informed decisions based on data. There are various methods to insert the data in the data warehouse, i.e., relational database, CRM, or any other integrated information system. The transformation of data in the data warehouse is based on a regular interval.
The graphical representation of data is known as data visualization. It is used to represent the data in a form that anyone can understand. There are plenty of tools and methods in data visualization, and it uses systematic mapping between graphic marks and data values to create the best-in-class visualization.
Data integration is the way that is used to combine the data from different sources such as devices or online databases into a single database. Data integration involves lots of steps such as cleansing, ETL mapping, and transformation.
It is used to conclude the causal connection based on the condition of an effect’s occurrence.
Graph summarization is where we summarize the graph's data in a form that can efficiently be used for the data analysis process.
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