When we look from the perspective of organizations and compared with previous years, we see that there has been very serious investment made in data management. In particular , we have seen that large projects such as digital transformation and modernization (cloud, big data etc) are taking place in the corporate world, and with the increase in legal requirements, there is a Data Governance solution takes place on the agenda of many institutions. In this article, I wanted to write something about this, based on these basic needs. I hope you found this article useful.
Fundamental Business Priorities and Challenges Encountered
When we consider the basic business priorities from the perspective of organizations, we see 4 important topics:
When we want to fulfill these business priorities that I mentioned above, we encounter some problems and challenges?
Increasing/Changing Customer Demands: Particularly when we consider the constantly increasing and changing demands of customers, it poses great challenges from the view of organizations For example: When we look from the perspective of younger generation, convenience, more affordable prices and face-to-face communication is more important, while the demands of the customers in the older segment are more personal and wider services to make their lives easier.
Technological Compliance: With the introduction of smart phones into our lives in today’s conditions, it is of great importance that the products and services offered are quickly accessible in other environments. At the same time, with the widespread use of social media, it is also became imperative customers to request services through these channels and to be contacted through these environments. At the same time, it has become a necessity to make investments in technologies in organizations in order to process these data in big data environments since data is continuously increases.
Data Management: Well, will increasing and ever-changing customer demands and technological investments be sufficient for this? Of course, it will not. As we think the past, we can see that organizations have continuously made high investments in applications and technological infrastructure, however organizations have encountered and still encountering significant data quality problems in both reporting and analytical studies such as segmentation because of the fact that data is not given required importance or in other words data is disregarded. In addition to this, due to the continuous increase of our data and the increasing demands from business units, rapid adaptation has gained great importance.
External Challenges: Apart from the above-mentioned items, there are also increasing external challenges, such as the challenging global conditions, compliance with legal requirements, security, and permitted communication.
Changes in customer demands, technological needs, problems encountered in data and increasing competition and legal requirements bring some fundamental challenges. And these fundamental challenges have negative effects, form the perspective of organizations, on efforts of many different departments, such as marketing, sales, customer service, for retaining existing customers, catching up-sell & cross-sell opportunities, offering the right customer through the right channels, and thereby increase revenue.
On the other hand, the approach of these institutions to the above-mentioned fundamental challenges reveals that the existing organizational structures and processes of organizations should be reviewed, internal policies and standards should be determined and technological investments should be made at this point. This brings us to Data Governance, which is our current issue today. In line with the above information;
- What is Data Governance?
- What are Main Factors and Projects?
- The Role of Technology
- Organizational Structure
What is Data Governance?
Data governance is an entirety of methods that enable end-to-end management of data within the organization. Accurate, consistent and timely , by engaging processes, policies, standards, technologies and people it aims to the most accurate decisions are taken in the most appropriate way.
If we categorize Data Governance according to the definition that we give above, it can be classified under 4 important headings.
Main Factors and Projects
In addition to the above-mentioned issues, when we examine what are the main factors leading the organizations to handle the issue of Data Governance, the following main topics come to the fore:
The Role of Technology
Although the importance of technology in data governance solution is significant, organizations that want to implement this solution should invest in the following technologies:
- Access to data from source systems (Access);
- Clean data for accurate decision making and reliable reporting (data quality);
- Determining the relationship between data (data model);
- Managing Master Data (master data management);
- Mapping and merging data;
- Transforming data according to business needs (Transformation);
- Managing and defining metadata (metadata management);
- Helping business units understand data (business glossaries);
- Workflow management (Workflow);
- Managing the life cycle of data (data security, data archiving, etc.)
Considering the importance of these technologies;
Data Governance Organizational Structure and Roles
Although the organizational structure varies from one institution to another In terms of data governance, in general;
- Executive Sponsor: It provides the necessary resources, funding and support for the organization’s data governance program.
- Data Management Council: Representatives of business units who define data governance strategies, policies, standards; as well as define person responsible for data, relevant responsibilities and project proposals.
- Business Users: They are people who use data within the organization. They work together with business analysts to identify business requirements related to data generated in the organization.
- Business analyst : They are responsible for defining needs arising from business needs to IT.
- Data Supervisors (Steward): Data supervisors are responsible for managing the data. Data supervisors are not owners of data; instead they are obliged to maintain the data. Data Supervisors are responsible for ensuring the quality, accuracy and security of the data.
- Data Analyst: They are responsible for defining details of data, managing data quality processes, establishing data quality rules defined by business analysts, and solving data quality issues as they emerge.
- Integration Developer: They are responsible for managing data integration processes and technologies to access the data required by business units.
At this point, if we write a few paragraphs about the roles and responsibilities of users in these roles;
I will end my article here and try to give details about a technology that provides a solution for data governance in my next article.