What Is Data Profiling? Definition, Process, and Tools

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Data Profiling is the process of improving the quality of data. Essentially, it enhances the usability factor of the data. This is done by scrutinizing and revising the data to produce useful summaries. These then assist in determining irregularities that might make the data hard to find, or even understand, for the consumers. As a result, a company’s data that is not well-managed will affect its growth. The organization will waste precious time and money to make meaning out of their data. This will thus impact its expansion.

 

What Is Data Profiling?

Data Profiling can be defined as the method of evaluating the condition of the data to get an insight into its quality. This is done based on the data’s precision, comprehensiveness, uniformity, relevance, and availability.

 

You can join the relevant Data Science Certification Courses to become a Data Profiling expert.

 

How is Data Profiling Done?

Businesses incorporate software that generates data sets to eliminate bad data.  In particular, companies are able to make out the sources that initiate data quality problems. Subsequently, these issues are responsible for impacting the functional and economic success of the enterprises. So, the installed applications allow businesses to reduce these abnormalities in the data to ensure its overall health. Thus, they can make the most of ‘healthy data’ to warrant the smooth functioning of their organizations.

 

What is the Process of Data Profiling?

Companies are required to make decisions based on the data that they collect from various sources. So, it is obviously essential that the data does not contain inaccuracies or irregularities. Therefore, by putting the process of Data Profiling in place, businesses can fix any inconsistencies in the data.

Let’s look at the following steps that will help us to understand the process of Data Profiling –

• At the outset, Data Profiling tools collect data sources, along with the related metadata, to be analyzed.
• Then, the collected data is cleaned and structured in a unified manner. This means that variances and replications in the data are removed.
• Thereafter, the Data Profiling applications send information and relevant statistics to define the cleaned data set. The description presented via Data Profiling may contain details such as repetitive patterns, lowest or highest values, or risks involving data quality.

 

Thus, a Data Profiling analysis enables Data Specialists to ascertain foreign key relationships between data units.

 

Which Inaccuracies Does Data Profiling Highlight?

Data Profiling can underscore a range of imprecisions in the data. These are –

• Missing or unknown values, that is, null values
• Values that are unusually high or low, and are not within the normal range
• Items that deviate from the expected pattern
• Values that should not be in the data
• Spelling errors
• Data with incomplete or missing information
• Repeated data

What are the Types of Data Profiling?

Organizations must look at Data Profiling as a crucial method to help understand their data. In addition to being an essential factor for data cleaning, it also validates whether data is up to the mark.

 

Intending to improve data quality, data specialists normally consider the following three categories of Data Profiling.

1. Structure Discovery

This type of analysis helps to decide whether data is consistent and organized appropriately. By using statistical processes, experts can get structure-related information that is indicative of the reliability of data.

2. Content Discovery

This procedure evaluates the quality of individual rows of data. It aims to pinpoint systematic errors by closely considering separate features of the data pool. For instance, it can help to catch values that are incorrectly entered.

3. Relationship Discovery

As the name suggests, this type identifies the relationships – similarities or dissimilarities, as well as links – amongst data sets. Subsequently, this enables experts to establish connections between data items.

 

What are the Tools for Data Profiling?

Data Profiling tools offer easy-to-use ways that assist operators in examining large amounts of data effortlessly. With the help of these tools, users can analyze data seamlessly. Subsequently, they can discover the form and value of their data sets by assessing their quality and consistency. Thus, these tools help to reduce manual effort to a very large extent, thereby saving the operators’ time.

 

Let’s look at some Data Profiling Tools

1. IBM InfoSphere Information Analyzer – This tool helps to assess data quality and accuracy at numerous levels.
2. Talend Data Fabric – This enables the users to explore data structures, identify traits, and explore relationships between items.
3. Dataedo – This is a tool that assists the operators in ensuring data quality. They can use sample data to identify data stored in the resources and whether it is of good quality.
4. Alation Data Catalog – This helps the experts to quickly decide the quality of any data object.
5. Informatica – This helps enhance data quality by analyzing, profiling, validating, and cleansing data.
6. Atlan – This tool allows businesses to make out the correctness, arrangement, quality, and comprehensiveness of data. Users can tailor data quality reports and set benchmarks for each data set.
7. Aperture Data Studio – This tool helps the operators to summarize, clean, and report on data quality.
8. Global Ids Data Profiling Suite – This tool automatically identifies data resources, automates data profiling, and provides a list of all data resources.

 

How Does Data Profiling Benefit Companies?

There are an array of advantages that organizations can reap via Data Profiling. One of these is procuring superior and reliable data after eradicating duplicate and irregular details. This can improve the usefulness of information, thereby assisting companies to make better professional decisions and estimate the future well-being of the organization.

 

Additionally, it can help to prevent minor slip-ups from turning into major blunders. Also, by providing a clear picture of a business’ condition, it can show the probable results of new situations. Consequently, this enhances the company’s decision-making ability.

 

Moreover, it is responsible for linking data that exists with the data that is missing. Also, it helps to establish which data is necessary. Thus, based on these analyses, it becomes easy for companies to fix their long-term goals along with a strategy to achieve them.

 

Future Scope of Data Profiling

Data Profiling is an essential component for improving business-related decisions. Therefore, companies have increasingly been hiring trained professionals with apt expertise.

These include –Data Engineers / Analysts / Scientists.

In order to have an edge over others in this field, the above-listed professionals must equip themselves with the right skill set. They can do this by joining a Certification Course in data science/management.

 

Best Data Science Course

Henry Harvin Education is a renowned Higher EdTech institute. Having trained more than four lac learners, it is an established EdTech company with a global outreach. It offers 1200+ training courses across more than 37 categories. Among these are its popular programs in Data Science and Data Analytics.

Here are the details of Henry Harvin Education’s Data Analysts Course.

Course Highlights

• First of all, it offers live online classes that are interactive.
• Furthermore, it provides easy access to e-learning material via Henry Harvin’s E-learning Portal. This contains PPTs, quizzes, a question bank, projects, videos, practice tests, doubt sessions, and the final assessment.
• The trainees become skilled in Python, R, and SAS. Also, they obtain mastery over statistics and mathematics. Besides this, the training gives a comprehensive knowledge of algorithms and makes the learners proficient in Excel.
• Moreover, it provides a guaranteed internship that equips the learners with practical experience.
• Also, the training allows for working on industry-based projects.
• Additionally, it offers access to numerous Masterclass Sessions for soft skills enhancement.

 

Conclusion

To ensure greater confidence in a company’s data, Data profiling is a must-do process. As discussed above, it facilitates an organization in better decision-making. Consequently, businesses can aim for higher employee output, improved customer experience, and greater profits.

 

Recommended Reads

1. What is Data? Definition, Types, and Uses
2. Top 25 Data Analytics Interview Questions and Answers in 2024 [Updated]
3. What is the future of Data Science & Artificial Intelligence?
4. Data Science in Daily Life | Data Science with Henry Harvin in 2024 [Updated]
5. How To Start A Career in Data Science in 2024 [Updated]

FAQs

Q1) Are Data Profiling and Data Mining the same?

Ans.) No, they are quite different. Data Profiling helps us to understand data and its features. Whereas, Data Mining helps us to see patterns in the data after analyzing it. 

Q2) How can I become a Data Profiling expert?

Ans.) You can join a course in Data Science or Data Analytics to start with this career. 

Q3) What is the duration of the Data Analytics course?

Ans.) A professional certification course in Data Analytics is for 11 months. 

Q4) Are data management courses expensive?

Ans.) The fee for these courses ranges between 1 lac and 1.5 lac. 

Q5) Can I do data management courses online?

Ans.) Most institutes offer degree or certification courses in Data Science and Data Analytics online as well as offline.

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