Data in organizations has become a significant risk issue. In recent years, new risks have emerged that have led many organizations to centralize their data and seek out new ways to mitigate their data risks through tighter data governance.
Organizations face new data risks
Regulatory change, like the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the US, have focused on data privacy. These have increased the level of financial risk for organizations that don’t manage their customer data well. Organizations can face fines of up to EUR 20 million or 4% of their global revenue, so they’re thinking about where their data is, who’s got access to it and if it’s being used in the right way.
We’ve also seen a myriad of examples over the years where decisions have been made off a spreadsheet with a single error that have cost businesses millions of dollars. Having good data governance and ensuring your data quality is high is now an important issue for organizations.
Data security and the risk of data loss is also increasing. For example, Equifax’s data breach has highlighted how data loss exposes organizations to reputational and regulatory risk.
These three factors are making organizations think about the best way to manage their data - the proof is in the rise of the Chief Data Officer. This centralized role is focused on data governance - managing and mitigating risk around data within an organization.
Really, the only place to manage the quality and security of your data is to manage it centrally. This is why we’re seeing organizations move towards centralized enterprise analytics solutions. Organizations don’t want to put their data out in the field on the desktop, they want to centralize it and keep it secure. With web technology, there’s also no reason for it to sit out in the field anymore.
3 ways to mitigate your data risks
In addition to centralizing your data, there are three effective ways that you can mitigate your data risks.
First, don’t move your data around. If you're creating copies of your data and shipping it all over the place, you’re creating risk. To mitigate this you need to keep your data and analysis in one place. This means you can’t rely on desktop analytic tools like Tableau and Qlik.
Secondly, you need to ensure that the only people who have access to your data are those that can and should have access to it. To ensure you can provide easy access to data for analysis but still control what people can see, you need to have row level security. This makes sure that sales managers on the east coast can only access customer data on the east coast, for example.
From a governance perspective, it’s also important to have consistent business logic for your data. You don’t want to have five different definitions of what a customer, product or revenue is. Everyone in your organization should have the same conversation about data. To do this you need to ensure that the rules and business logic that is being created around your data is consistent and applied equally to every piece of analysis. This is achieved through a metadata layer. It creates business rules within an application, so when people are analyzing data they're all working within the same logic and business paradigms.
By ensuring your BI tools and teams have these three things you can govern and manage your data more effectively and minimize your data risks.
BI Data Governance: The secret to successful business decision making
Find out how to lay the foundations of a comprehensive BI data governance that will maintain trust in your data so your business can make the best decisions. Download the paper by Barry Devlin, founder of the data warehouseing industry.