Data filtering is an essential tool for businesses of all sizes looking to make better insights-driven decisions. It takes complex data sets and narrows them down to only the key elements needed for an analysis. This process helps businesses make faster and more informed decisions, taking advantage of the vast amount of data that exists today. This blog post will explore what data filtering is, how it works, and why it is so important for businesses looking to stay ahead of the competition. In addition, it will review the benefits of data filtering, the different types of data filtering, and the best practices for implementing data filtering in an effective and efficient way. Businesses of all sizes can use data filtering to make better decisions and achieve success in today’s data-driven world.
Excel Sorting and Filtering Data
What is data filtering used for?
Data filtering has a wide range of potential applications across numerous industries. The following is a list of several applications for data filtering in IT:
You can process records and count the number of records that meet specific criteria with the aid of data filtering. For instance, you can use data filtering to extract only the male customers who reside in Ohio from a list of 500 customer names if you want to determine how many male customers there are overall. Then, marketing experts could use this data to develop targeted advertising campaigns.
Data filtering is another tool used by IT professionals to change or replace values. For instance, if your company routinely imports data from outside sources, you might want to replace all external IDs with your own internal IDs. By doing this, an internal ID rather than an external ID will be used for all imported records. To update older data or remove older files, you can also filter data by the most recent modified date.
Evaluate a dataset
Data filtering is a tool used by IT professionals to assess the quality of a dataset. Data filtering, for instance, can assist IT professionals in verifying that all records are true, accurate, and current. It can also determine whether the values in a particular field satisfy certain requirements. Fields can be compared to one another or to a list of values already in existence to accomplish this.
Create new structures from old datasets
Data filtering is a technique used by IT professionals to create new structures from older datasets, and then they apply logic and algorithms to transform the structures into different forms. Data filters can be used to clean data before importing it into a program or to break up a large dataset into smaller groups for analysis. For instance, you could use data filtering to look for data with outdated logic and update it as necessary.
Exclude a field or values
Additionally, IT experts use data filtering to eliminate specific fields or values. For instance, you can easily apply your criteria using data filtering if you want to exclude female customers who are 75 years of age or older, as this is a restriction set by your organization’s policy. Similar to that, you might want to eliminate all documents that have a specific keyword in the title.
What is data filtering in IT?
Examining a dataset to remove, reorganize, or distribute data in accordance with specific criteria is known as data filtering. For instance, data filtering might entail calculating the total number of sales for each quarter and removing records from the previous month. Data filtering is frequently used by IT professionals to fulfill their duties and aid others within their organization in data analysis.
Benefits of using data filtering
Due to the numerous advantages of data filtering, many organizations advocate for its use. Here are some benefits of using data filtering:
Improves efficiency of IT processes
It is possible to speed up the process of validating and cleaning up existing datasets by using data filtering. Before importing data into your system, data filtering can also help you create new sub-datasets or otherwise alter an existing dataset. By resolving data issues before they have a greater impact on productivity, data filtering may also enable IT teams to save time in the future.
Allows for better data security
Data filtering is a tool that IT professionals can use to make their systems safe. You can use data filters to create requirements for adding credit limits to users, onboarding new users, and other crucial user requirements for the organization. For instance, you might demand that new users register only after meeting certain requirements, like submitting documentation of their identity and address.
Reduces redundancy and unnecessary data
Data filtering, as the name implies, can assist you in removing extraneous data. Data filtering, for instance, can be used to eliminate all records that contain either type of field in order to determine the total number of records in a dataset with two different types of fields, such as integers and strings.
Example of data filtering
Here is an illustration of data filtering being used by an IT team in a made-up company:
Software company Archibald Technologies creates and markets a project management tool. A small team has been formed by the business to carry out project management tasks, such as gathering data on all of the organization’s projects. The rest of the team, aside from the project managers, is only involved in processing reports for recently finished or upcoming projects. The team decides to implement a new data filtering technique that will enable all team members to eliminate redundant data from their reports.
The IT team adds a new field called “Status,” which is given an integer value of 1, 2, or 3, to start the data filtering process. All reports produced by one or more members of Archibald Technologies may have this field filled out. The next step is to include a filter in the “Status” field. The filter substitutes the strings “Recurring,” “In Progress,” or “Completed” for integer values.
What are the types of data filters?
When data is filtered in Microsoft Excel, only the rows that satisfy specific criteria are shown. (The other rows gets hidden. If you want to see data from the store where the Shoe Size is 36, you can set a filter to do this.