Data governance can be considered to be the key factor for data driven companies. The three major sectors where data governance could be important in the future is artificial intelligence, big data and the internet of things.
Why is data governance important for your business?
While there is lack of proper data governance, it proves that there is poor quality data. Poor data will lead to inconsistent definitions, duplicates and even some missing fields. Let’s see the importance of such data governance services.
- Data governance saves money:Data governance increases the efficiency of the system. While duplicate data leads to duplication of efforts and the sheer wastage of time as far as marketing, sales, finance and also analytical efforts are concerned. After all, when you save time, your money is also saved.
- Bad data governance proves to be risky: The lack of security concern is mainly effective for two reasons. Firstly, it’s associated with dirty and unstructured data that clogs your database. You may quickly tell when something is at risk and maybe things happening around your database.
- Data governance provides clarity:While providing effective data governance it provides peace of mind and the fact that the data is clean, accurate and also standardized. You will see some benefits that the clarity of data will provide. There will be assurance that the metric is accurate and also measure your KPIs. The insight of most of your metrics might be true. There will be greater confidence in your analytics.
How do you set up a data governance program?
- Identifying roles and responsibilities: The role of data governance is handle a set of questions along with answers. It’s all about forming a framework that helps the producers and consumers collaborate with ease and utmost security.
- Defining the data domains: You will have to identify the data domains, data types and various data elements that governs the system. You can identify the various additional stakeholders that should be included in your operating model.
- Establishing the data flows: You will have to identify the data as a supply chain. You will have good understanding of the data informing report and also begin to prioritize the data. Analyzing the fact where data comes from and where it ends up to is most important.
- Establishing data controls: This is the place where you can establish appropriate data controls and optimize the data’s quality along with integrity. You can define data controls, metrics as well as threshold.
- Identifying the authority: You can identify the data source and establish the purpose of report thereby prioritizing the key data elements. Data source should be the most authoritative source for that report that goes forward.
- Establishing policies with standards: The policies and standards have to be rolled out much more widely. You can clearly communicate roles and responsibilities as well as align policies with the broader data of institution’s management strategies.
For achieving the purpose of data intelligence all organizations have to adopt a data governance program. While starting small, they can build a momentum and the foundational program can achieve goals to data governance.