Effective decision-making is characterized by a connected, contextual, and continuous process of analyzing information, prioritizing goals, and taking action. As it stands, correct data at disposal is the only sure-shot way of making that a reality.
When the talk’s about “correct data,” it’s not just limited to gathering information — it’s about how you prioritize goals and make decisions rooted in evidence.
The modern workplace is rapidly becoming more data-driven, with metrics and performance evaluated in a more precise, quantitative capacity. So, it’s not enough to simply know about data. You need to be able to see the connections between your metrics in a way that helps you make decisions.
And that’s where the need for data governance becomes paramount. It propels
organizations’ success and growth by connecting strategic, tactical, and operational
decisions. Global Industry Analysts Inc. (GIA) predicts the data governance market to reach a market value of $6 billion by 2026. Indeed, the capability to govern data
effectively will be a key deal-breaker for organizations in the future.
On that note, this post will talk about the whats and whys of data governance and how it helps you outsmart your competitors.
Need for Data Governance and Its Role in Ensuring Correct Data
The quality of data is key to making informed decisions and, consequently, the success of an organization. But organization’s data assets are valuable only when they are valid and utilized properly. Often, poor quality data ends up hampering an organization’s potential and competitive advantage.
To that end, data governance defines the principles ensuring the identification of quality data in an organization. Here’s how:
- It describes the processes, roles, responsibilities, and metrics to ensure an enterprise’s accountability and ownership of data assets.
- It delineates the course of action, the choice of data, the defined parameters, and the methods used.
All in all, robust data governance enables faster and wiser decisions. Following are the essential factors that serve as the key components for effective data governance:
- Data Quality
- Data Management
- Data Software Tools
- Data Security
- Data Compliance
Data quality largely depends on how it is collected, planned, analyzed, and processed. Most data analytics leaders fail to assess, measure, and monitor their data and its analytics. Only organizations with data governance measures in place can focus on and achieve compliance-oriented goals.
That said, optimizing data quality is the first step toward the road to data governance. Once an organization has established a culture of sharing, tracking, and standardizing information, other aspects like data management and software tools can be considered.
Data management is essentially the execution of data governance strategies. It sets forth the responsibility for implementing standards and policies for data governance. Typical tasks in data management include:
- Creating role-based access to data by creating access levels
- Implementing data governance policy rules
- Establishing and maintaining the data security of the data owned by the organization
- Adopting appropriate measures to minimize risks associated with storing sensitive data
- Creating a master data management system that gives a single view of data across the enterprise.
Data management is key to data inventory; it lets organizations have methods and strategies for accessing, integrating, storing, transferring, and preparing data for analytics.
In fact, effective data governance is a direct product of data management maturity. It resolves questions like – what data should an organization manage and where should it be stored? Should it be on-premise or on a third-party cloud?
Data Software Tools
Data has to be taken care of properly and kept safe and secure. And this is made possible by using the right software tools that can be relied upon as solutions. An example would be using third-party services, especially when storing data in the cloud or on-premise devices.
Appropriate software solution tools help organizations maintain a consistent set of policies, processes, and data ownership. The process lets them monitor, manage, and control data movement effectively.
Moreover, these solutions help users establish guidelines, rules, and accountability measures that ensure standard data quality. Data governance tools also provide recommendations to help increase efficiency and streamline processes.
Countless malware threats and ransomware attacks affect businesses globally, costing organizations billions of dollars. Studies suggest that such attacks result in companies paying an average remediation cost of more than $1.8 million for every security breach.
A large amount of data at disposal can further complicate the matters. For organizations with legacy platforms having rich data sources, these tend to create siloed information making it difficult to identify the source. The silos are often exported to the organization’s database and duplicated to combine data with other existing siloed data.
This makes it even harder to know the data source and its destination!
Favorably, data governance defines an organization’s data management rules and prevents potential leaks of sensitive business information/customer data from falling into the wrong hands.
The governance process analyzes confidential data and sets systematic architecture traceability. It lets the concerned team determine the data source, establish its route, identify those who have accessed it, and trace how it has been used.
Data governance and compliance work hand in hand. Data grows and matures quickly, to the extent that data compliance has to be addressed and taken care of by organizations. They have to be compliant with what regulations in their government they belong to.
While the European Union has GDPR (General Data Protection Regulation), the US constitutes the well-known:
- PCI DSS (Payment Card Industry Data Security Standard)
- HIPAA (Health Insurance Portability and Accountability Act)
- SOX ACT or Sarbanes–Oxley Act of 2002 (also known as the Public Company Accounting Reform and Investor Protection Act).
These regulations require organizations to trace their data from the source up to its obsolescence, identify who has access to it, and know how and where it is used. That said, effective compliance can only be realized with a holistic approach to your data governance strategy.
Major Data Governance Success Stories
Google Leadership Development Program
Google focuses intensely on what it refers to as its “people analytics.” One of its well-known people analytics initiatives, Project Oxygen, saw Google mining data from more than 10,000 performance reviews.
The Data was then compared to that of employee retention rates. Google used the information to identify common behaviors of high-performing managers.
Subsequently, they created training programs to develop these competencies in others.
The exercise helped boost median favorability scores for managers from 83 percent to 88 percent!
Driving Up Sales at Amazon
Amazon uses data for its product recommendation based on prior purchases and patterns, buying history, and search behavior. Amazon uses its customers’ data analytics and machine learning to drive its recommendation engine effectively. A significant part of Amazon’s consumer purchases is tied back to the company’s recommendation system!
Ellicium Data Governance Advantage
By now, we’re well aware that it’s time to reengineer decisions making them more connected, contextual, and continuous. For organizations to be responsive to opportunities and disruptions, there needs to be a sound Data Governance strategy in place. This calls for the use of expertise, the right tools, and of course, managing the compliance and security factors.
At Ellicium, we carry out the gamut of data governance and management for effective business results that reflect on the balance sheet. We are dedicated to driving business transformations using big data analytics and artificial intelligence.
Most importantly, we are open to anyone reaching out to us to draw a practical vbig data implementation roadmap, providing big data managed services, and helping with data lake implementation.
Get in touch with us for a free 30 minutes introductory session on data governance and see how we can work together to reimagine your data.