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Blog / How To Master Your Data Governance With Adverity

How To Master Your Data Governance With Adverity

If you’ve been working in marketing or data management for any length of time, you might have come across the term “data governance”. 

But what is data governance, and why is it important? 

Explained simply, data governance refers to the implementation of guidelines, standards, processes, and accountability for the management of data within an organization. It covers all aspects of data management, including how data is created, collected, processed, stored, controlled, and made available for analysis. 

Having a solid data governance strategy can help ensure that your data is accurate, secure, and compliant with data privacy regulations. It also helps ensure that data is suitable and accessible for different teams across your business, enabling them to make informed decisions.

Without the right processes and guidelines being enforced, you run the risk of inconsistencies and inaccuracies that can lead to a lack of trust in your data for business decision-making and leaves your business open to the implications of non-compliance with data privacy legislation. 

So, being able to master data governance is clearly important. 

Yet 80% of businesses claim to be struggling to understand what data they have, how it’s used, and who owns it

In this article, we’ll take a deeper look at the reasons why data governance is so critical for businesses, establish the building blocks of effective data governance, and talk about some of the features within Adverity that can help you implement a robust strategy. 

The importance of data governance

Data governance is important for all businesses. But it becomes more critical as the volume and complexity of your data increases. 

It’s simply not feasible to maintain confidence in the consistency, compliance, or accuracy of data that’s being managed across a dozen or more different sources, without having a data governance strategy in place.

As the complexity and volume of data evolve within your business, the tools and strategies you use to manage it need to evolve too. The measure of how advanced your data management practices are is often referred to as “data maturity”. 

Improving your data maturity and taking the time to master data governance is important for a number of reasons. 

Improved data quality, leading to better decision making

Having a solid data governance foundation is essential if you’re going to be confident about the quality of your data for accurate analysis and effective business decisions.

Without a strong data governance strategy, you are more likely to struggle with data inconsistencies and inaccuracies which can reduce the ability of teams across the business to extract meaningful insights from your data.

A lack of data governance can prevent the development of a data-driven culture within your organization, as people across the business may not trust or effectively use the data available to them.

Improved controls over access to data

Access control is another important aspect of data governance. Making sure the right people have access to the right data at the right time can speed up the decision-making processes and improve your organization's ability to respond quickly to business needs and changing market conditions. 

Established data governance policies are also essential for the prevention of security breaches and unauthorized access to data. 

By establishing policies and processes around the confidentiality, access, and availability of data, your organization can make sure that sensitive data is only accessed by the correct people within your business, and only certain people have the ability to alter it. 

Compliance with regulations

Being able to master data governance is also crucial for compliance with regulations such as GDPR.

Non-compliance with data regulations can lead to legal complications, significant fines, and damage to your business reputation. This is obviously the worst-case scenario - but without a documented data governance strategy, it can be challenging to demonstrate that your business meets these regulatory requirements.

Improved collaboration across the business

By establishing clear data governance policies, you can also ensure data is collected, stored, and used in a consistent way across all teams in your business. 

This can help foster a culture of collaboration within your business, with all departments working from the same data for more effective decision-making and data governance strategy. 


The 7 building blocks of data governance

Data governance can be a complex area of data management, and if you haven’t been through the process before, it can be tough to know where to start.

To help, we’ve summarized a previous article we’ve published on the 7 building blocks of good data governance.

1. Data access

The first step to master data governance is to define who has access to certain types of data, and what they can do with it. 

Data governance, management, and control of access privileges are particularly important if your business is processing Personally Identifiable Information (PII), as you need to ensure that access to sensitive data is tightly controlled to protect the privacy of your customers and comply with data regulations. 

But this first building block isn’t just about restricting permissions, it’s also about ‘data democratization’ - making sure that the people who need access to specific data can access it easily, so they can make the insights and decisions they need to make. 

2. Data unification

One of the biggest data challenges for a lot of businesses is having to access, analyze, and compare data by logging into a variety of different sources. Not only is this time-consuming, but it also increases the likelihood of inconsistencies and errors in analysis and decision-making. 

That’s where the second building block of good data governance comes in - unifying and consolidating your data so it’s all in one place. Getting this step right means that the following building blocks can be completed in a more efficient and scalable way.

3. Data classification

Once you’ve unified data from your various different sources, it’s important to properly classify it. 

Not all the data you’ve consolidated will have the right classification or formatting - some datasets might have lost their original data types during the process of unification. 

Therefore, you should evaluate your consolidated data and ensure it’s classified and formatted based on the correct data type, such as dates, text strings, whole numbers, decimals, currencies, or percentages. 

This can be a time-intensive process, which is why businesses that manage a large amount of data often opt for automated tools to help speed up the process and remove the potential for human error.

4. Data enrichment

This data governance best practice involves ensuring consistency in the way your data is analyzed and compared, which is important if you’re going to maximize the value of your data. 

Imagine you’re bringing in three different sets of marketing data that all measure performance differently. One measures ‘Cost Per Conversion’, one measures ‘Return on Investment’ and the other doesn’t have any defined performance measurement - just the conversions and revenue generated. 

It’s going to be difficult to accurately compare the three channels without a consistent measure of performance. 

This is where data enrichment can help. Using the example above, you could take the costs and revenue from each of the three datasets and create a consistent ‘Return on Ad Spend’ calculation in your consolidated data, which gives you an effective measure to fairly and accurately compare the performance of each campaign. 

Data enrichment isn’t just about joins in data - it also involves strict data governance to make sure things like naming conventions are all consistent to help users across the business more easily search and sort through data.

5. Restructuring of data

If you’re used to analyzing data across multiple platforms, you’ll be familiar with the frustrating experience of different sources having different descriptions and names for what is essentially the same thing. 

The amount spent on a marketing campaign might be called “Cost” in one platform, “Spend” in another, and “Budget” in another. 

The process of restructuring these variations in data naming through data mapping is another data governance principle that helps ensure you’re in the best position to effectively compare the same data from multiple sources.

6. Data reconciliation

Errors and inconsistencies in your consolidated data can undermine the confidence and trust in a centralized database to make effective business decisions. Or, in the worst case, if errors are left undetected, it can lead to misinformed and erroneous decision-making. 

That’s why it’s important as part of your journey to master data governance to implement data reconciliation as a quality control measure. 

By regularly comparing the metrics in your consolidated data against the original data source, it helps deliver confidence to the entire business that data is suitable for making important decisions, and it also helps you to proactively identify and address any inconsistencies and errors.


Benefit from robust data governance with Adverity

Adverity is an integrated data platform that is specifically designed to help marketing teams harness the power of their data and improve the quality and speed of their data-driven decision-making.

The platform includes a wide range of features and functionality that can support businesses with the implementation of a robust data governance strategy

Smart naming conventions

Smart Naming Conventions is a powerful feature that enhances your data governance strategy by ensuring data consistency. 

It does this by enforcing agreed naming conventions across your data, making sure that every variable that is being consolidated from your different data sets meets the rules and criteria that you stipulate in your data governance policy. 

Smart Naming Conventions can split data like campaign names based on an agreed delimiter and ensure that each variable in the data set matches the criteria set in your agreed format.

So if you’ve set the rules to expect a numerical value in a certain field, and a text value gets passed through instead, Smart Naming Conventions can either alert you to the inconsistency or withhold the upload until the error is fixed.

By enforcing consistency in this way, Smart Naming Conventions help maintain data integrity, improve data quality, and enhance your overall data governance strategy.

Anomaly detection

Another important data governance feature within Adverity is the anomaly detection that is included within Proactive Analytics. 

Our advanced artificial intelligence uses historical data to build an understanding of what the expected range is for all of your important business metrics. 

If a value falls outside of this expected range, the system will alert users in their dashboard so they can investigate the issue in a timely manner.

By alerting users to unexpected discrepancies in data as early as possible, anomaly detection plays an important role in maintaining robust data governance.

Authorizations and access

Data access management and data democratization are both important if your business is going to master data governance. 

Adverity contains features that can help your business succeed in both of these areas. 

Within the ‘Authorizations’ section of our dashboard, you’re able to centralize the management of all your different data sources, and also determine which users can make edits to the data streams that you have set up. 

This helps ensure that no unexpected or unauthorized changes are made to the data that is being consolidated. 

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In addition to the Authorizations section in the dashboard, Adverity also enables you to set up different workspaces which can contain different subsets of your data for different roles within the business. 

For example, you may have a “Marketing” workspace that contains only the marketing channel data, a “Website” workspace that only contains data from site analytics and your eCommerce platform, a “Customer Success” workspace that contains just CRM data, and a “C-Suite” workspace that contains access to everything. 

This level of customization for data access can help ensure that teams have access only to the data that helps them achieve success in their role and avoids any distractions or irrelevant data. Having these access controls also ensures that sensitive data only reaches the right people. 

Activity monitor

Another feature we offer that helps businesses implement effective data governance strategies is the Activity monitor. 

This section of the platform dashboard lists all the recent data-fetching tasks and provides an overview of whether they were successful or not. If there’s a failed task, the system can be configured to alert you right away so you’re able to quickly investigate the issue. 


Within the Activity Monitor, there’s also a “Performance Manager” that provides a detailed breakdown of how long each data fetch took to be successfully integrated into your data destination. 

By keeping an eye on the performance manager, you can quickly spot any common data connections that are taking longer than others to integrate and begin to investigate the issue so that your data is always as fresh as it can be. 



Examples of effective data governance

Implementing a robust data governance strategy is important for any business that is managing data from multiple sources.

To help illustrate how effective data governance can help improve business performance, we’ve put together an overview of two of our recent client success stories. 

Territory Media

Territory Media is a Munich-based full-service agency whose capabilities range from strategic consultancy to media buying and the management of digital campaigns. 

The agency was facing data governance challenges in maintaining data consistency due to the number of disparate data sources they were manually accessing and analyzing to optimize campaigns. The process of manual reporting was time-consuming and prone to human error, and the lack of real-time data access was a barrier to fast decision-making. 

Territory Media worked with Adverity to address these data governance issues by consolidating data from different platforms into a single source of truth, with the necessary transformations and enrichments to ensure that data was consistent and could be used to its full potential. 

By automating the process of data integration with Adverity, Territory Media was able to monitor client KPIs in real-time, streamline their decision-making process, free up significant resources previously used for manual reporting, and ensure the consistent and effective use of data across the business.


"Before we used Adverity, campaign optimization could only be done in the respective department of the business units. It took the departments up to 2 days to prepare the monthly reports. Short-notice customer queries, for example on overlapping KPIs, entailed significant additional work,...Thanks to automated reporting, we can now use the freed-up resources to optimize existing campaigns and also answer short-term customer queries quickly and in real-time."

Agnieszka Kutyla

Head of Data & Analytics, Territory Media



Read the full case study

Vodafone Germany

Vodafone is one of the largest telecommunication companies in the world, with a marketing presence in Germany that spans over 20 different channels and 150 different digital campaigns. 

With such a vast amount of data across different marketing channels, Vodafone found that although their campaigns were successful, performance data was in data silos, was inconsistent, and required a lot of manual work for meaningful comparisons and analysis to be drawn. 

Adverity helped to address these data governance challenges by automating the integration of data from the different data sources into a centralized data lake, enabling real-time insights from business data that was not possible before. 

The outcome of Vodafone’s partnership with Adverity was a significant reduction in the amount of business resources (both time and budget) that were being spent on data extraction and an 80% increase in data quality within the business. 

"With the multitude of marketing campaigns we carry out at Vodafone each year, excellent management is essential - not only for the success of each campaign but also for its efficient implementation and analysis... That's why it was of the utmost importance to not only bring management in-house but also to optimize the data quality and the quality of the resulting analyses. Thanks to our collaboration with partners such as Adverity and AWS, we are now able to do exactly that - and still save massively on costs."

Philipp Rathmann

Senior Data Analyst, Vodafone Germany



Read the full case study


Ready to take control of your data governance with Adverity?

Mastering data governance and implementing an effective data management strategy can help ensure that your business data is accurate, secure, compliant, and optimized in order for your teams to make fast, effective decisions. 

The seven building blocks we’ve covered in this article will provide you with a solid foundation to approach the process, but to truly master data governance you’re likely to need the right integration and monitoring tools to support you. 

Adverity is an integrated data platform that includes a number of features that can help you implement an effective data governance strategy. 

If you're ready to elevate your data governance and unlock the full potential of your data, book a demo with Adverity today. 

Make insights-driven decisions faster and easier!

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