Alon Reznik

Data governance is the ongoing process of managing the availability, usability, integrity and security of corporate data.

To achieve this, businesses must create internal standards and policies that control data usage, quality, and consistency . In addition, it must ensures that data doesn’t get misused.


Why is Data Governance so critical right now?

The importance of data analytics for business operations

Organizations are increasingly reliant on data analytics to optimize operations and drive business decision-making.

Businesses strive to make the most of every possible data source to get a clear picture of their product performance, their business KPIs and their customers’ behavior.

To achieve this, they must embrace more and more data sources, both internal data and from third-party platforms or data providers.

With great power comes great responsibility. Having access to data that might be sensitive or confidential (such as personal information or billing details) means they need to be careful about the way in which this data is stored, managed and used.

Besides this, not all data is created equal.  Flaws alongside the processes of data transformation or manipulation might alter the data and provide misleading information when data isn’t handled correctly.

With so many data sources, and companies trying to aggregate so many data points to create bespoke KPIs, it isn’t unusual for mistakes to happen along the way – which in essence end up delivering misguided data.


Data privacy regulations

Data privacy regulations are getting tougher. This is understandable, with the influx of data being used by companies. There’s also the the recent high profile scandals which uncovered how companies didn’t do enough to ethically protect user data.

Without robust data governance processes in place, it can get pretty hard to keep track of how your data is being stored, managed, or used.

This is particularly true for organizations in which data isn’t unified or centralized. This often leads to different teams or data silos adhering to different standards when it comes to data management.


What are the benefits of investing in robust data governance strategy? 

1) Data Quality

You can’t compromise on the quality and integrity of your data. Discrepancies are commonplace, especially as data moves between relational databases and its sliced, diced, and transformed to create business insights.

There are platforms in the market such as quilliup which are specifically designed to help running ongoing data validation tests throughout your data pipeline. These can provide timely alerts for your teams as and when there’s a data quality issue.


2) Data Efficiencies

Data silos and not streamlining data processes can end up costing companies a fortune. Yes, it might be annoying to initially create a centralized data hub that connects all your business data sources into a single data warehouse.

But the benefits far outweigh the costs in the mid term. In addition, having a single source of truth won’t only save you time and money by avoiding duplicate work. What’s more, it will also ensure all your business teams or units are consistently relying upon the same insights.


3) Data Control

Taking control of your data is imperative. Data management platforms like Rivery are designed to help any organization orchestrate and manage all their data. Without controlling all your data streams, you can’t really make the most of your business data.

When it comes to data governance, controlling all your processes and how they’re being handled is essential. Whether this is looking at historical data logs or changes, organizations need the tools to get full visibility on their past and present data processes – also key for compliance purposes.


4) Data Trust

All your stakeholders must trust your data. This isn’t only in terms of accuracy but also trusting the way in which you handle data that might potentially be of a sensitive or confidential nature.

Recent data scandals such as Facebook’s, which this week admitted it wrongly shared user data with 5,000 developers, have raised awareness about how sensitive data can be easily mishandled – and the consequences of doing so.

New regulations such as GDPR mean companies have to be more cautious about the way they store, manage and handle user data. Ultimately, respecting your data (including data privacy) means building trust – among customers, users, investors, or employees.


Where do I start? Who is responsible for implementing data governance?

Data governance is likely to involve everyone in an organization to different degrees. Data company Profisee identifies four main stakeholders that should be involved in this process:

1. Data Owners

Data owners are ultimately accountable for the state of the data as an asset. People that are able to make decisions and enforce decisions throughout the organization.


2. Data Stewards

These data “champions” will make sure that the data policies and data standards are adhered to in daily business. These people will often be the subject matter experts for a data entity and/or a set of data attributes.


3. Data Custodians

These operators will be responsible to make the business and technical onboarding, maintenance and end-of-life updates to your data assets.


4. Data Governance Committee

Main forum for approving data policies and data standards and handle escalated issues.

Data Governance isn’t a buzzword or a fad. In fact, new research projects that the data governance market is expected to register a CAGR of over 21.44%, during the forecast period, 2020 – 2025. The market is expected to reach a value of USD 5.28 billion by 2025.

To some companies, “Data Governance” sounds like a scary process to police processes and audit data, when in reality it’s more about establishing the right infrastructure and processes for your business to leverage their data with confidence.