Data Governance a Key Enablement to Data-Driven Organizations

Today any organization is producing a numerous amount of data every day. No matter how big or small are these data but means a lot to get a value from data. Data Governance is a must to ensure sustainability of organization data driven transformation.

To be a data-driven organization means that your business relies on effective data to make decisions for better profitability.

Data-Driven Organization (DDO) is a culture that treats Data as an Asset. Differentiating and competing on data and analytics, Collaborating through data for business improvements.

So, a DDO must a Data Driven Culture to embraces the use of?data?in decision making

All speak the same language about data, everybody knows about the data, everybody trusts the data, everybody talks about data?

A data-driven culture builds tools and skills, builds users’ trust in the condition and sources of data

McKinsey "A healthy data culture is key to amplifying the power of your data"

However, culture is very important but also organizations maturity in data management, data architecture, data operations, data quality, data security, more technical considerations and standards that must be exists in a DDO. All of this domain aspects come under an organization Data Governance Maturity Level.?

Data Governance

A Key to Data Enablement that should be under an enterprise governance following up on the business strategy delivered by the organization data strategy and is an important part for sustainability of organization data driven transformation

The?DAMA Dictionary of Data Management?and the #DAMA DMBOK defines?data governance?as: "The exercise of authority, control and shared decision making (planning, monitoring, and enforcement) over the management of data assets.”

The?Data Governance Institute?(DGI) defines the Data Governance in a short definition as “Data Governance is the exercise of decision-making and authority for data-related matters. “

So, Organizations must treat data as its assets

In order to be able to obtain the right data management process, data governance should help organization define, and communicate right policies, procedures for protecting and managing their data in proper way.

• Without proper Data Governance it is hard to develop and implement it an effective Data Strategy or modernize your data management
• Data is the Company’s Assets and it should be owned by business
• Data must be protected and secured

Why Data Governance is important and is a Must to an Organization ?

It brings people together to cooperate, work to the same goal and speak the same language of data.

So the goal is to enable business to define standards and processes that guides managing their data in a protected way. It helps improve the data quality to extract the real value of the data.

It also helps reduce the risk of operations with cost optimization and comply with regulations and standards as GDPR.

?McKinsey?puts it this quote “For data to fuel digital initiatives, it must be readily available, of high quality, and relevant. Good data governance ensures data has these attributes, which enable it to create value.”

What is a Data Governance Framework?

Here’s how the?Data Governance Institute?(DGI) defines a data governance framework: “The data governance framework is a logical structure for classifying, organizing, and communicating complex activities involved in making decisions about and taking action on enterprise data.”

According to the?Data Governance Institute (DGI), every organization must have:

• A set of?rules?(policies, requirements, standards, accountabilities, controls) and the?rules of engagement?describing how different groups work together to make and enforce these rules
• The?people and organizational bodies?making and enforcing those rules
• The?processes?that will govern data while creating value, managing cost and complexity, and ensuring compliance

From our point of view, a minimum 6 components in a Data Governance Framework should be included:

Data Leadership: Support & Foster a Data- Driven Culture with responsibility of apply a Data Governance framework, guide all the stakeholders and organization culture implementing the policies and standards.

Data Stewardship & Ownership: Defined Data Accountability & Responsibility. Stewards are the subject matter experts and data practitioners, while the Data Owners who has the rights for accessing or editing data and is responsible for protecting a data domain.

Data Architecture: A data mapping to all sources whether structured or any other type to be consolidated to single source of truth, and manage the modeling /design of enterprise data sets to guide the data engineering / integration, storage, control and operations

Modern Data Management (MoDM): Manage your data warehousing, storage, processing, analyzing, Big Data, DataOps, data development & engineering, Meta data Management, Analytics, BI

Data Literacy & Culture: Knowledge & Common Understanding of Data Assets by improving the data awareness for both business and techno teams for technology and technical tools

Data Quality: Trust & Confidence in high Data Quality by doing DQ measurements of integrity, completeness, consistency, accuracy, validity, and uniqueness. Define your GQ Rules for profiling and data validation and measure quality improvements.

Data Privacy and Security: Data is an asset, so must be protected, secured under established policies on how data is collected, stored, extracted, shared, controlled, used and accessibility.

It can drive through from Organization People, Process, the rights to which systems, the data bases or data sets behind these systems, understanding each element through business glossaries, data catalogue, data Linage on highly protected quality of organization data.?

Data Governance on Cloud

When it comes to transforming data into cloud, Data Governance is a critical concern as organizations are allowing hosting their enterprise data at risk by leveraging the data to travel to a far-away location. Data should be protected and governed as it is the company’s assets. Cloud data governance goes on an additional dimension of complexity in multi-cloud or hybrid cloud computing environments, where data is found in multiple places and data governance protocols (authorizations, policies, metadata, data dictionaries, etc.) are inconsistent amongst data sources.

It is recommended to standardize the policies of data access, well understand all the data elements with enhancing the organization metadata, measure the data quality and apply DQ rules to have more high quality of data, comply with regulations such as GDPR. IT is very important to ensure Data security, protection, retention policies to the cloud data.

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