What Is Data Profiling and How Marketing Agencies Can Benefit from It

What Is Data Profiling and How Marketing Agencies Can Benefit from It

Marketing agencies deal with data on a daily basis, and the quality of this data is critical to their success. However, data quality continues to be a key reason for failed campaigns, and disappointing client experiences. In the following we are going to discuss what is data profiling and how can it be leveraged in order to achieve the aforementioned success; how you can put in place a robust data profiling process for your organization.

Manual methods of refining data are unable to keep pace with the growing volume and complexity of enterprise data. To maintain data quality, you need to have an automated, software-defined data profiling process in place. 

The impact of bad data


Bad data quality has a real impact on your business. According to Experian Data Quality, ‘75% of businesses are wasting 14% of revenue due to poor data quality. Other research by Software AG and Lemonly states that bad data costs organizations 10-25% of their revenue. According to Informatica, a leading data integration company, the loss of revenue could be as high as 30% (as reported by Ovum Research).

Whichever way you look at it, bad data costs you anywhere between 10-30% of your revenue. The consequences of bad data are real, and this is a challenge that needs to be resolved by organizations that deal with large quantities of data, especially marketing agencies.

The benefits of good data


Research by BackOffice Associates found that organizations that took measures to fix their data quality troubles saw a 10% increase in productivity, 57% increase in customer satisfaction, and 20-40% increase in overall sales. Therefore, the benefits of good data quality have ripple effects across the organization. This is not surprising considering every team - Sales, Marketing, Support, or Product - all rely on data to make operational decisions on a daily basis.

So, while data quality is bad news for most organizations, it can profit those companies that diagnose the issues accurately and decide to fix this nagging problem; which clearly requires knowing what data profiling is. But, even if you want to take action on your company’s data quality, the first question is where you should start.

The first and most important step to ensuring high quality data is to have a data profiling process that governs all the data in your organization. But, what is data profiling?

What is data profiling?


According to TechTarget, “Data profiling is the statistical analysis and assessment of data values within a data set for consistency, uniqueness and logic.” Another explanation, according to Oracle is, “Data profiling analyzes the content, structure, and relationships within data to uncover patterns and rules, inconsistencies, anomalies, and redundancies.” Data quality is affected if your data has duplicate records, or if it is inaccurate, or incomplete. Data profiling ensures an organization’s data doesn’t suffer from these errors.

Data profiling checks various aspects about the data and evaluates its quality. It looks to identify anomalies in the data, and gives you a ‘profile’ of the data, so you can work towards improving its quality.

The process of data profiling


Let’s look at some of the attributes that data profiling checks for. This will further explain why data profiling is so important to enterprises.

1

Duplicate data

Data profiling would check the number of duplicate and unique entries in a data set. You ideally want to have all unique entries. For example, in an email subscriber list, any duplicates mean that your list is artificially bloated and your subscribers could receive two emails from you every time you send out a single email. This is not good for you or your subscribers.

2

Outliers

Inaccurate data can skew the output of any analysis on that data. Often, a couple of outliers can skew the result greatly coming to a completely different outcome.

outlier

Source: Laerd.com

Now, outliers when genuine, are important data points to include in your analysis, but often, these outliers could be because of an extra ‘0’ or ‘1’. Imagine the confusion this could cause if the numbers you were analyzing were advertising costs, and you assume that you’ve spent way more than you had budgeted for. In these cases, you need to check if the outliers in your data are legitimate, or errors. Data profiling can help you identify these inconsistencies.

3

Data Formats

unstructured content

Research by Recommind shows that unstructured data makes up 80% of all data in the enterprise.

The typical marketing agency is dealing with various data formats in their systems. As these systems interact with each other, the clashing data formats can make it hard to derive meaningful conclusions from the data. For example, if your customer support system allows users to input data via attachments, and users sometimes upload data in formats that the system is unable to recognize, this can affect your analysis of support workloads. In these cases, you need to check the format of data, and make sure it is recognizable by the system.

4

Relationships across columns & tables

As a marketing agency, you deal with numerous clients, and each client has a number of campaigns running simultaneously. You, naturally, deal with a lot of data. This is especially true if you have access to your client’s end user data too. When analyzing large data sets, the key to deriving value from the data is to spot the connections between the data. On the other hand, if the data is disconnected, you will find very little insight from it.

Data profiling lets you spot patterns, and connections across the various columns of a table, and even across tables with different data. This context gives you insight into how one data point can influence another seemingly unrelated data point. This kind of advanced data profiling is very difficult to perform manually, and can only be done with a purpose-built data profiling tool.

That brings us to talk about the traditional and modern approaches to data profiling.

The traditional approach to data profiling


Previously, enterprises used to have teams dedicated to data profiling. They use SQL queries, and commands in spreadsheets to manually look for errors. They would typically check a sample set of the data, and once satisfied, they’d assume the rest of the data is clean.

They needed to be hawk-eyed to catch minute errors in thousands of rows of data. For example, when comparing the gross revenue with sales volumes of a retail store, they may find a discrepancy. They would have to comb through thousands of rows of data to find the mismatch. This is draining on the people who used to do the data profiling, and is very inefficient, often not ending in the desired result.

The modern approach to data profiling


With the advent of algorithms, noSQL databases, and advanced filesystems, the same job done by teams of data experts is now offloaded to software tools that do a much better job of data profiling.

These tools scour through data at rapid pace, and can easily find errors and inconsistencies in minutes or seconds, which would have taken humans hours or days to spot. Not to mention, the tool would cost you just a fraction of the spend on a data profiling team.

Conclusion


Considering the importance of data profiling, and the possibility of using a modern approach to data profiling, every marketing agency needs a data profiling tool. It gives you greater visibility into your client data, and equips you with the right data to run your campaigns. All this will result in happy clients who see you as an active partner with them as they look to derive more insight from all the data at their disposal.

Once you’ve utilized data profiling and are confident of the quality of data in your systems, you need a business intelligence (BI) platform to analyze all your data. You need a BI tool that can be extended across all teams in your organization. It should be versatile enough to analyze any data type, and any amount of data you throw at it. At the same time, it should be intuitive and easy to use so even the busiest executive can use it on a daily basis. Allocable is an option if you want an easy to use BI software.

Allocable gives you deep visibility into data across your organization, and lets you optimize your resources for maximum output. As a marketing agency you need every team and role within your organization performing at peak levels so you can keep clients happy, and reap higher revenues. Allocable gives you a lens on your workforce and projects so you know what’s going well, and what isn’t. It lets you get a top-level view of your data by team or project, and lets you drill down to the details and find ways to improve. As a marketing agency, a robust BI tool like Allocable is no longer a luxury, it is indispensable.

View a demo of Allocable to get started today.

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Allocable is a cloud-based automated time tracking and business intelligence (BI) software platform that provides  a complete visualization of your workforce and project productivity data empowering you to turn information into actionable insight to optimize and forecast performance with more certainty.

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