Technological advancement of the 21st century has brought about rapid digital transformation. The change is unprecedented, from how we socialize to how we do business. Health, politics, and education, among many others, are not left out of the changes. As a result, we’re more informed, connected, and efficient in what we do.
At the core of digitization is a massive amount of data (creation, capturing, and storage). Statista estimated that 180 zettabytes of data will be created globally by 2025. Access to this data enhances fast decision-making, which is vital to improving rapidly-growing economic issues.
Thanks to readily accessible data, modern businesses can now customize their products and services to better suit the needs of their customers. Marketing campaigns are more personalized, and the entire production process is more efficient.
However, with easy data accessibility, businesses now face a new challenge regarding effectively storing or managing big data without compromising customer, client, or employee privacy. A proactive solution to this challenge requires good data governance initiatives.
You may be asking, what is data governance? How does it impact the entire organization’s data security, management, and storage? Our guide will answer these questions and why data governance should matter to your business.
Data governance involves an organization's approach to establishing a structure for how data passes through the entire organization.
Data governance encompasses monitoring data quality and establishing protocols for collecting, processing, organizing, sharing, securing, and using data. The idea is to ensure your company can make the most of the data that passes through it while complying with laws and regulations.
Therefore, data governance is the set of policies and procedures that defines how a company interacts with data.
Data governance ensures the right data goes to the suitable business units at the right time. This can improve the company’s data analytics and management.
Modern business enterprises require good data governance for two significant reasons:
We detail these two reasons below.
It’s difficult for businesses that work with large volumes of enterprise data to maximize its use and achieve strategic objectives using ordinary means.
Before data can inform your business decisions, you must ensure its quality. Certifying the quality of data on your system alone requires sorting through the hundreds of thousands (or even millions) of data fragments. Then you have to organize them and merge them from across the different collection sources or platforms. Next comes the analysis of all the data you have collected and organized so far.
Unfortunately, this is not a one-time process either. Data is continuous, and only through an elaborate system can any business hope to effectively manage its perpetual data flow.
Before a company can even start dealing with data of such magnitude, the stakeholders or data governance teams have to create a system to manage the data and its processes. You have to establish which channel to receive data from, which analysis methods and tools to adopt for a specific data model, which employees to grant data access to, etc.
The user data in your possession needs adequate protection. Guaranteeing data privacy and security is one way a business can retain customers’ trust and maintain integrity among stakeholders. Customers’ trust equates to loyalty. When customers are loyal to your brand, they buy more and recommend your brand to friends and families. The net effect is increased revenue. However, that’s not the only reason why businesses prioritize data integrity or privacy. Another core reason is to avoid sanctions or prosecution by relevant authorities due to privacy violations.
The reason is that each country’s government has regulations that guide how organizations can collect and use data. For example, the General Data Protection Requirements (GDPR) of the European Union set rigorous guidelines for how the data of its citizens can be captured, stored, used, and shared.
Several state and federal laws in the United States, like the Health Insurance Portability and Accountability Act (HIPAA) and the Electronic Communications Privacy Act (ECPA), put the same regulations on the way the data of US citizens can be used or protected. They create data standards that must be strictly followed.
Failure to comply with these regulations can lead to heavy and costly sanctions from the law. Any company found handling customers’ data with negligence will lose customer trust.
The need to adhere to laws and regulations provides an added incentive for businesses to have an accountable and organized system shaping how it handles data.
Below are the four pillars of data governance that highlight its significance.
Data stewardship involves executing the framework and structure provided through effective data governance. It includes techniques and methods of collecting, organizing, distributing, and sharing data. Data stewardship also encompasses the various roles and responsibilities within the data management framework.
The entire data lifecycle within the data governance framework will be meaningless if there is no way to translate its principles and policies for everyday use.
Data quality deals with how much value a particular data set contributes to your objectives. This involves how accurate or reliable the information is, the timeliness and order you received it, and how comprehensive the data is.
Data quality addresses the completeness of data presented. It deals with issues of incomplete phone numbers, missing entry fields, and general errors made when inputting information.
The usefulness of data to any organization is a matter of its quality. High-quality data contribute to the policies and decision-making process of a business tremendously. It guides appropriate decision-making and precise actions to get ahead of the market.
Master data management (MDM) involves administering and centralizing the core data categories essential to achieving your business objectives.
Master data is generally grouped under four domains for businesses. The primary domain is the customers — which covers employee data, products, location, etc. The “other” categories cover domains like contracts, warranties, licensing, etc.
Master data management is essential because data is collected from multiple sources through several tools and devices into a single data storage silo. Therefore, the new data must be organized and sorted into master data domains to be useful.
The following are specific applications of data governance and how they improve efficiency and progress:
Data governance tools help systemize, develop protocols, and bring structure to an organization’s data usage and management. Below are some of the most essential and popular data governance tools available to businesses:
Some typical data governance roles in a company include:
An efficient data governance initiative is the recipe for good data management. Nevertheless, companies need to take further proactive measures to secure sensitive data. For instance, while listing old company phones for resale, you need to carry out an enterprise-level data wipe. When buying used replacement phones in an open market, you must get a mobile device history report. Prevent sensitive information from getting into the wrong hands for the resale phone through the data wipe. The history report validates the phone’s working conditions and ESN status for the replacement phone.
Unfortunately, most IT managers don’t know how to go about this. That’s where Phonecheck comes in. Our industry-standard diagnostic software offers data wiping and mobile certifications at an enterprise level. Our software solutions guarantee data security and integrity, whether you’re reselling, buying, or carrying out routine company mobile device checks. Avoid costly hidden problems by purchasing an individual device history report on phonecheck.com for about the cost of a cup of coffee.
