According to the Data Governance Institute, data governance is "the exercise of decision-making and authority over data-related matters." In other words, it is the control over every data entry that must be done according to certain standards.
In the future, companies will focus more on data governance anddata quality because the data is only useful if it is easily accessible and actionable. The balance between data access and security is instrumental in working in an agile manner and adapting to changes in the business.
Enterprise data preparation software, tools, and methodologies will help strengthen this trend and narrow the gap between business and technology. Data governance can help foster a culture of analytics and better meet desired business needs.
For example, the implementation of self-service business intelligence capabilities has led to major Excel-like governance issues for many companies.
So, business departments will seek to bring more trust and reliability into analytics practices. More collaborative processes will be created to help both IT teams and end users align and implement modern data governance models and maximize the business value of analytics without compromising security.
In recent years, we have unfortunately witnessed quite a few data breaches which have led to an increase in security issues related to governance and trust. To improve business outcomes, organizations have begun to view data governance as a necessity, but the lack of experience presents them with challenges in implementing and combining data quality, risk, ethics, privacy and security to create reliable business value, according to Gartner.
Data governance brings the human layer to the automated and data-driven system landscape. Through predefined and targeted rules of conduct, companies can create precise conditions for data management so that certain criteria relating to law, protection and compliance are guaranteed.
Compliance with legal requirements such as DSGVO in the EU (EU General Data Protection Regulation) or industry-specific requirements is ensured through ongoing compliance.
A strategically balanced and thoughtful data governance plan improves
- the accuracy
of data used across the enterprise.
Data governance realizes a consistent and constant way of working and viewing the data. Business departments retain their flexibility and versatility, although the common understanding of the data is strengthened.
Customer analytics is one of the key focus areas of data governance or business intelligence. Customer journey analysis, emotion recognition, customer lifetime value, speech analytics, interaction analytics, analytics for customer intelligence are some of the buzzwords of this trend.
"By 2021, 15% of all customer service interactions will be handled entirely by AI, a 400% increase from 2017" - Gartner.
By predicting customer behavior, the use of data becomes an essential part of the customer experience and its formula for success. Gartner has developed a hype cycle to analyze the most critical technologies in the supporting customer process, as many executives are on the lookout for technologies that deliver the CX (customer experience) customers want.
As the expectations of consumers increase, it is a challenging task to support their requirements by leveraging big data collections. Analyzing and predicting their behavior goes hand in hand with data management, AI, and cloud.
Becoming more data-driven and using analytics tools to leverage the most effective way of making decisions is becoming a prerequisite for sustainable business development. Consumers will dictate this evolution, so we consider it one of the most important trends.
As mentioned above, companies produce huge amounts of data about customers, customer behavior, employees, clients, patients, etc. This data must be used appropriately to analyze the market more effectively and to better understand the behavior of the relevant target group. This data must be used appropriately to analyze the market more effectively and to better understand the behavior of the corresponding target group. These insights are crucial to the success of the business. Data governance helps to comply with legal requirements and to make the data available to the appropriate user group in a secure and confidential manner. Structure, security, documentation and usability are essential features.
By means of Data Governance, companies minimize their error rate with regard to their data and increase their productivity!