5 Practical Steps to Improving Data Governance

February 25, 20202:01 pm2202 views
5 Practical Steps to Improving Data Governance
5 Practical Steps to Improving Data Governance

While the concept of big data is not new, it is just recently that companies are recognising the importance of doing more than simply storing and managing their data. More and more companies are on their way to develop data governance policies and stewardship functions as part of their IT operations. 

Why data governance? 

Different from big data which helps analyse a large amount of data across diverse platforms, data governance helps in decision making, monitoring, and enforcing body that has authority over data management. In other words, data governance helps businesses scale data value chain and turn a large set of data into meaningful, actionable insights. Without a formal data governance strategy, businesses are bound to face multiple challenges that can pile up and eventually collapse. 

According to I&I survey, without data governance, there are 4 significant risks, including delayed decisions and inability to make the right decision for business output or employee experience. As a consequence, businesses could suffer from a great productivity and performance loss. 

Another study by Profisee on Data Management Report found that among the top 5 data management initiatives, data governance helps organisations get a high quality of data to decide what’s right and what’s wrong, what matters and what doesn’t for company’s and employee’s success, by centralising and labelling all files, as well as ensuring that all information has been cleaned. With the help of data governance intelligence, organisations could create data safety within the workforce, ensuring there is no data breach. 

See also: 3 Risks of Data Analytics and How to Prevent It

How to improve and cultivate the success of data governance? 

While learning from experts could be the best practice, you still have to adapt the data governance practices as a different system applies a different strategy. To start, here are five practical guidelines you could implement. 

1- Set priority 

There are specific sections in business, such as sector that priorities in regulatory compliance or risk management. It is advisable for you to focus on one or two of these sections. Focusing on a certain area will give a more effective result that can bring utmost immediate benefit to an organisation.

2- Maximise availability and create roles 

Data cannot be governed if it is not readily available and accessible. Thus, there should be an effective database and authorised experts to securely view and edit data to readily accessed. Once your data is ready, you should determine who does what with certain data. 

According to The Data Governance Institute, there are different focus areas in data governance, including those that focus on management alignment, on data warehouse and business intelligence, architecture or integration, etc. That said, you should make a team that focuses on a certain area depending on the business needs. Each individual on the team should hold a different role and responsibility to focus on reporting the right result and recommendation for which data or information should be integrated. After that, the team should share the information with the company’s IT professionals for further action needed to cleanse the data. 

3- Improve and ensure information integrity 

This is a crucial step in developing the right data governance. In this step, you should make data work for you by following these four processes, as advised by the Information Builders report. The ability to implement these processes in real-time is key for ensuring data integrity. 

  • Data profiling to define good and bad data. To analyse quality trends, profiles must be compared continuously against previously profiled data. 
  • Parsing and standardisation to validate and correct both industry-standard and organisational-standard attributes within the data. 
  • Data enrichment to create scoring and profiling results for information and implement business rules for scoring and profiling. It also gives you the ability to add additional data. 
  • Monitoring data to get the updated result. This steps also helps show where information quality suffers, so-corrective processes can be implemented sooner than later. 
4- Establish infrastructure and convert the culture 

Process alone will not ensure the integrity of information, but people do. Hence, establish an accountability infrastructure that holds people accountable for information assets and provide them with the technology they need to ensure the integrity of the assets. 

When you are able to build the best infrastructure, it is time to migrate to data-based culture. In a data-based culture, you can gather stakeholders to discuss a particular invoice. Most organisations today are truly transaction data-based in their perspectives which keeps them from leveraging the maximum potential of their data to support businesses.  

5- Encourage feedback 

Feedbacks help you get continuous improvement, allowing your data governance to get better from time-to-time. You will also get the maximum result of the above processes while driving your businesses to those assets. 

“The success of data governance ultimately depends on people. When people know their roles, responsibilities, and the rules, focus on master data and are supported by technology that makes it easy for them to do their jobs, data governance works.” – Information Builders 

Read also: What is Data Mining & How Safe It is for Your Data Safety?

(Visited 1 times, 1 visits today)