06/09/2017 | Skriven av: Gästbloggare
Categorized: AI & Watson | Kognitiva lösningar
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Unified data governance is becoming a critical strategy for data-driven organizations
Mention data governance to a developer and a chill might run up their spine. Historically, data governance, the management of data access within an enterprise, has been seen as a time consuming, complex task with minimal long-term value to an organization. Yet along with the emerging role of the CDO (chief data officer), integrated and unified data governance is becoming a critical strategy for data-driven organizations.
Why does data governance matter?
Gone are the days of data governance applying only to highly regulated industries like healthcare, finance, and government. The amount of data available to organizations has skyrocketed in recent years, according to IDC the total amount of data worldwide will hit 180 zettabytes by 2025, and the chief data officer has become a critical member of any organization’s executive team.
CDOs strive to succeed in five areas:
- Creating enterprise-class data
- Building data science assets
- Developing an integrated cloud strategy
- Attracting top talent
- Achieving integrated and unified data governance
Data can be an organization’s biggest asset, but only if it is properly classified and in the hands of the right stakeholders. This is why data governance is so important to the CDO — it’s their job to ensure each stakeholder has the data they need to make better business decisions. By classifying data based on type, level of risk, etc., an organization can unleash the potential of its data in a safe and compliant manner.
The five step program for a unified data strategy
So how does one get started on a successful data governance strategy?
Step one, classify your data: In order to prevent legal ramifications that come with misrepresenting data, it is essential to properly classify all data within your organization. It can take up to six months to complete this process, but the end result is worth the time invested because identifying the risk associated with each piece of data is critical to compliance.
Step two, identify who has access to what data: Develop a data hierarchy within your organization so each employee has access to the data set they need to excel at their job. Determining this will depend on the employee’s role, department, level and other factors. For example, the finance team will need to have access to data on year over year company growth so they can plan budgets accordingly.
Step three, determine the policies associated with each piece of data: After determining who has access to what data, define the various policies associated with each data set. If data cannot be moved to another country due to differing data policies, be sure international employees do not have access.
Step four, catalogue and convert policies into code: Once data policies have been identified and employees assigned access to proper data sets, create a data policy catalogue and convert rules to code in order to automate processes. This will create a single data governance policy for your organization. Creation of a codified catalog of policies allows for the proactive application of data policies. All the previous steps were necessary to enable this. Applying policies proactively is required in order for governance to be an enabler. Policies should be allied as API’s whenever data is called for access or movement.
Step five, collaborate on data: Now that the unified data strategy has been solidified, different business units can collaborate to make better and more strategic decisions, resulting in significant business impact. Through open source tools within an organization, the teams can collaborate across data sets to better understand data and its value.
Where does your organization fit into the Five Phases of Information Governance Maturity? Take the assessment and get your results.
Taking the burden off developers
While developers may think achieving data governance is a roadblock for their teams, it actually lifts a weight off their shoulders. Without a data governance strategy, it is the responsibility of the development team to make sure the data is protected and in the hands of the appropriate decision makers.
With a data governance strategy, developers don’t need to worry about handing over data to the correct teams because the process is automated.
As all organizations become increasingly data-driven, a successful data governance strategy is not a roadblock, rather it accelerates productivity and streamlines data processes. Not only is data governance a benefit to organizations, but it is also a requirement as companies can be fined up to 4 percent of their revenue for not being up-to-code. Data governance is key to putting the power of data in every employee’s hands.
Read more how Open Data can help you to Accelerate your Digital Journey.
/ Seth Dobrin, Vice President and Cheif Data Officer for IBM Analytics
If you have any questions, feel free to reach out to me on LinkedIn.