In my previous article, I mentioned some basic concepts of data governance: (Link):
- Key Business Priorities and Challenges Encountered
- What is Data Governance?
- Main Factors and Projects
- The Role of Technology
- Data Governance Organizational Structure and Roles
In this article, as I mentioned earlier, I will talk about the data governance approach and Informatica solutions that provide solutions in this regard.
Data Governance Approach
When we consider the Data Governance approach, we will see 4 main steps. Discovery, Define, Apply, Measure and Monitor.
If we explain these topics from perspective of the data quality approach example;
- Discovery Conducting of detection/discovery of data quality problems in accordance with the analyzes performed on the data
- Define : Defining of data quality rules in accordance with the data quality problems discovered in previous step.
- Apply Developing of defined data quality rules
- Measure and Monitor: And finally, with the help of scorecards, data quality reports or KPIs created, making the relevant measurements and following the whole process.
Data Governance Requirements
On the basis of Data Governance Approach, when we consider that what were needed for this purpose, we can say that;
- Understanding the data content and identifying the critical data (Understand)
- Identification, understanding and categorization of data assets (Catalog)
- Associating data assets with each other (Connect)
- Determining roles and responsibilities and managing them with the help of business processes (Govern)
- Managing of those by ensuring collaboration between IT and business units (Collaborate)
- And ensuring implementation of all these mentioned requirements (Execute) were main needs
The Role of Technology in Data Governance
As I mentioned in my previous article, the importance of technology in data governance is very important, however, to summarize the requirements at this point:
- Data Integration : Access to data and transformation of data according to business needs
- Data Protection : Masking of data in accordance with relevant sensitivities
- Information Lifecycle Mng. : Management of data life cycle and archiving of unused data
- Master Data Management : Management of reference and master data
- Data Quality Management : Determination of data quality problems and follow-up with related corrective actions
- Asset Catalog : managing metadata information in different systems within the institution organization.
- Data Security Analytics : Discovery of sensitive data and generating of risk scores
- Collaborative Governance Wrk. : Identification of data assets and management with the help of business processes
Informatica Data Governance Solutions
Informatica’s solutions for data governance in accordance with the technologies that I mentioned above are as follows.
Informatica data governance solution is consisting of integrated technology components, which are fed by data quality, metadata management and data security, which are the most significant components in terms of data governance, where data is identified and controlled by Axon at the uppermost tier in line with the business requirements concerned with data governance.
Thanks to this, the relevant data governance processes are managed in accordance with the steps in the data governance approach (Discovery, Define, Apply and Measure and Monitor) that I mentioned at the beginning of the article and between Axon and other modules (Data Quality, Data Security and Metadata Management -EIC- ) these processes can be integrated as you can see below.
Benefits Provided by Informatica Data Management Solutions to Departments
At this point, I will sum up the benefits of Informatica’s solutions for data governance to different departments:
By finishing my article here, I will be talking about each technology component in more detail, starting with the Axon solution in my next article. I hope you found tis study useful.