What is Data Profiling and How Does it Make Big Data Easier?

Data comes from various sources, and how successfully you profile your data is crucial. According to data quality assessments, only around 3% of data fulfill requirements for quality. As a result, businesses lose millions of dollars due to mishandled data, lost opportunities, time, and resources.

This is where Data Profiling comes into the picture. It is a powerful tool that ensures quality data through the act of monitoring and cleansing data to improve data quality and gain a competitive advantage in the marketplace. This article delves into the process of data profiling, highlighting its potential to transform raw data into valuable business data.

What is Data Profiling?

Data profiling is like giving data a check-up. It looks at information, breaks it down, and gives a summary that helps find problems, risks, and trends. This process gives a big-picture view, and companies can use what they learn to do better.

In simpler terms, data profiling checks if data is good and real. It uses smart math to figure out things like average, highest and lowest numbers, and how often something happens. It also digs into the details to find other important information, like how often things show up, what’s related, and what’s connected. Then, it looks at all this information and sees if it fits with what a business wants.

Imagine you have a list of customers, and some names are missing, or there are weird numbers. Data profiling helps catch these mistakes. It finds things like missing information, things that shouldn’t be there, and things that don’t make sense. This way, businesses can avoid costly errors and make sure their data fits with what they need and want to do.

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Benefits of Data Profiling

Data quality issues can significantly impact businesses, resulting in wasted revenue, recalculated strategies, and damaged reputations, often due to inadequate data quality. Bad data can cost businesses 30% or more of their revenue.

Well, sometimes, it’s because companies get so busy collecting data that they forget to make sure it’s good and useful. That’s where a data profiling tool comes to the rescue. Below, we have mentioned benefits of using Data Profiling.

1. Makes Data Better: The tool looks at the data and fixes any problems. It gets rid of things that are repeated or don’t make sense. This helps businesses make better choices and see where they can improve.
2. Helps With Smart Decisions: The tool uses the data to avoid small problems before they become big ones. It also helps predict what might happen in the future. So, it’s like having a crystal ball for your business decisions.
3. Avoids Problems Beforehand: The tool spots problems before they even show up. This way, companies can fix things quickly and avoid big troubles.
4. Keeps Things Organized: Businesses deal with lots of different data, like from social media or blogs. The tool checks where the data comes from and makes sure it’s safe. It’s like organizing a messy room so you can find what you need easily.

Data Profiling Tools

Data profiling tools enable the analysis of various data sets, including big data in real-time and structured and unstructured data, making massive data projects workable quickly. Some data profiling tools and their benefits are mentioned below.

1. IBM InfoSphere Information Analyzer

• Checks every part of your data.
• Makes sure important things, called keys, are correct.
• Sees how unique different values are in your data.

2. SAP Business Objects Data Services (BODS)

• Finds problems in data quickly.
• Combines different tasks, like keeping an eye on data quality and organizing information, all in one.

3. Informatica DF and Quality Solution

• Another tool that works fast and checks data very carefully.
• Helps IT teams by doing some tasks automatically and supports keeping data in order.

4. Talend Open Studio

• A set of free tools for data.
• Helps without needing to write complicated code.
• Finds patterns that could be signs of problems and shows them in easy-to-understand charts.

5. Oracle Enterprise Data Quality

• Has features like checking if data follows the rules, like a data police officer.
• Cleans up messy data and keeps things organized.
• Works well with other Oracle tools to keep everything in line.

Types of Data Profiling

Data profiling applications analyze databases by organizing and collecting information using techniques like column profiling, cross-column profiling, and cross-table profiling, which can be categorized in three ways.

1. Structure Discovery

• This is about checking if everything in your data follows the rules. It looks at how data is organized and if it makes sense.
• It uses basic statistics to see if your data is good and valid.

2. Content Discovery

• Think of this as making sure your data looks nice and is useful. It’s like fixing the format of things, such as addresses or phone numbers, so that everything works smoothly.
• For example, if an address is written in a weird way, it might cause problems delivering things or reaching customers.

3. Relationship Discovery

• This is like finding how different pieces of data are connected, almost like creating a family tree for information.
• It helps understand how different sets of data relate to each other.

Best Data Profiling Practices

Let’s talk about some basic and advanced things we do with data to make sure it’s good and useful:

Basic Data Checking

1. Distinct Count and Percent:

• This is like finding special keys and unique stuff in our data. It helps when we’re adding or changing things.
• Works well for tables without headers.

2. Percent of Zero or Blank or Null Values:

• We use this to spot missing or unknown data. It’s like having a backup plan in case something is missing.
• Helps set default values for our data.

3. Maximum, Minimum, Average String Length:

• This helps us pick the right sizes for our data. We don’t want our columns to be too big or too small—it’s like finding the perfect fit.
• Makes things work faster and better.

Advanced Data Checking

1. Key Integrity:

• This is like making sure our data always has the right keys. It helps find keys that are kind of lost, which can be a problem for future plans.
• Helps with organizing data and planning for the future.

2. Cardinality:

• Checks how different sets of data are connected. It’s like figuring out if one thing is related to one, many, or lots of other things.
• Makes tools that use our data work better.

3. Pattern and Frequency Distribution:

• Checks if our data looks the way it should. This is super important for things like emails or phone numbers.
• Ensures our data is ready for communication and sharing.

How to use data profiling using Excel?

Imagine looking at your data from a really high point, like 30,000 feet in the sky. It’s your first overview, helping you understand what’s in the data, how things are related, and if there are any problems. Here are some questions you might ask:

• Is the data accurate, or is something obviously wrong with it?
• Do we understand what each thing in the data is supposed to measure?
• Do we have all the data we need, or is something missing?
• If it’s in Excel, are there any formula errors that could mess up our work?
• Has all the data been copied correctly?

Data Profiling in Excel using Power Query:

In Power Query, there are features to help with data profiling in Excel. It’s like having tools to understand and clean up your data. You can find these features in the View tab of the ribbon under the “Data Preview” group.

Different Data Profiling Options:

• Monospaced and Show Whitespace:

To alter the data’s appearance in the Power Query editor, select “Monospaced” to display fixed-width text and “Show whitespace” to display leading spaces. Changes how the data looks in Power Query.

Column Quality and Column Distribution:

Check these two options you will get to see 3 options of “Valis, Error, Empty”. These options show you the quality of each column and the distribution of values.

Valid cells are those that are not empty and don’t have errors. Empty cells are really empty, marked as null in Power Query. Errors might happen if there’s a problem, like dividing by zero in a formula.

Column Profile:

• Gives you a detailed breakdown of each column, including charts and statistics.
• Gives a deep dive into a column’s values, including charts and statistics.
• Useful for understanding things like how many times each value appears

Column Distribution:

Shows a chart next to Column Quality, helping you understand how values are spread out.

In Excel, Power Query is a fantastic tool that makes understanding data much easier. It quickly points out if there are any numbers or words in your data that don’t look right. It also helps you figure out which parts of your data might be causing issues. But it doesn’t stop there – it even gives you a visual way to see how all your data is arranged. It’s like having a helpful assistant making sure your data is accurate and straightforward.

Data Profiling Examples

Let’s take the example of Domino’s, the world’s biggest pizza company. In 2015, Domino’s introduced a new ordering system called “AnyWare”. Suddenly, they had tons of data coming from all sorts of devices like smartwatches, TVs, and social media. With the help of reliable data profiling, Domino’s figured out how to handle all this data. Now, they use it to understand their customers better, improve their systems, catch fraud, and sell more pizzas.

Another example is Office Depot, a company that sells office supplies both online and offline. They use data profiling to check and control the quality of their data before putting it in their big data storage called a “data lake.” By combining info from their catalog, website, and customer call centers, they get a full view of their customers. This helps them provide better service and use their data wisely across the company. 

Data Profiling with Data Lakes and the Cloud

With companies putting lots of data in the cloud, using data profiling is super important. The cloud can store a crazy amount of data, and things like the Internet keep adding even more info from our homes, what we wear, and our gadgets.

To stay ahead in today’s market, especially with big data in the cloud, you need to be good at using all this information. Whether it’s following rules or giving excellent customer service, data profiling is the key to managing all this data and succeeding. It’s the difference between doing great and falling behind.

Conclusion

You don’t have to do data profiling manually. The smart way is to use a special tool that does it automatically. These tools make sure your data is right and consistent, which means fewer mistakes. Talend Data Fabric, Informatica DF and Quality Solution are some of these tools. It can take information from almost anywhere and put it in a safe place without needing lots of manual work.