What is Data Manipulation?
Data manipulation is the method of organizing data to make it easier to read or more designed or structured. For instance, a collection of any kind of data could be organized in alphabetical order so that it can be understood easily. On the other hand, it can be difficult to find information about any particular employee in an organization if all the employees' information is not organized. Therefore, all the employee's information could be organized in alphabetical order that makes it easier to find information easily of any individual employee. Data manipulation helps website owners to monitor their sources of traffic and their most popular pages. Hence, it is frequently used on web server logs.
Data manipulation is also used by accounting users or similar fields to organized data in order to figure out product costs, future tax obligations, pricing patterns, etc. It also helps the stock market predictors to forecast developments and predicts how stocks might perform in the adjacent future. Furthermore, data manipulation may also use by computers to display information to users in a more realistic way on the basis of web pages, the code in a software program, or data formatting.
The DML is used to manipulate data, which is a programming language. It short for Data Manipulation Language that helps to modify data like adding, removing, and altering databases. It means that changing the information in a way that can be read easily.
Objective of Data Manipulation
Data manipulation is a key feature for business operations and optimization. You need to deal with data in a proper manner and manipulate it into meaningful information like doing trend analysis, financial data, and consumer behavior. Data manipulation offers an organization multiple advantages; some are discussed below:
Steps involved in Data Manipulation
Below there are some important steps given that may help you out to get started with data manipulation.
Why do use data manipulation?
It is more important to manipulate data for improving the growth of any business and organization. As manipulation of data helps to use the information properly by organizing the raw data in a structural way, which is crucial for boosting productivity, trend analysis, cutting costs, analyzing customer behavior, etc. Below there are some examples of the benefits that describe the need for data manipulation.
Data manipulation offers a way to organize data in a unified format, which helps c-suit members to a better understanding of business intelligence. The collection of data from various sources can be unstructured, whereas DML (Data manipulation language) allows data to be consistently organized and more transparent.
The manipulation of data can help you with making the right decisions by providing easy access to data related to your previous projects. Also, it can help with required team size, budget allocation, and deadline projections.
The manipulation of data provides efficiency in terms of collecting organized data or meaningful information. You may not be aware that findings interfere or are redundant, information is relevant or not, metrics have a low or significant impact. DML offers you the benefit of isolating and identify these facts quickly.
In daily life, we also see data manipulation; if you are receiving calls from telemarketers, getting targeted ads on the websites you visit or receiving emails, it is all done through data manipulation. It also helps in your online behavior in terms of extracting relevant information. For example, when you are visiting any website and share your email address at this site and agree to terms and conditions, it will monitor your behavior and likely generate relevant data for you.
Data manipulation tips
One of the widely used tools for data manipulation is Microsoft Excel. Below there are some tips to work on this tool.
Difference between Data manipulation and Data modification
Both terms, data manipulation and data modification sound similar; however, they are not interchangeable. Generally, data manipulation is the act of organizing data to make it cooler to read or additional refined. On the other hand, data modification is the process of changing the existing data values or data itself.
Anyone can get confused by their sound; therefore, here is an instance to explain both terms. Let's take value X=7. It can be represented by data manipulation as X=3+4, or X=2+5, X=8-1, etc. By using data manipulation, it can be represented as X=5.