Ema Castellari, Data Governance & Analytics Project Manager, COA, Argentina

Ema Castellari is a Data Governance & Analytics Project Manager at COA (Argentina) and Hiberus (Spain). She holds a degree in System Analyst from UTN, and has completed several postgraduate courses in BI and Data Governance. Her last certification was CDMP Practitioner Certified (Dama). She has worked in BI for over 15 years in several industries such as retail, public administration, bank, etc, and started to work in Data Governance approximately 4 years ago supporting organizations to define their Data Strategy through global Data Governance programs, managing them as strategic assets, promoting the democratization of information, in an end-to-end vision that includes the development of data in the complete life cycle, reducing costs and increasing their profits, ensuring optimal decisions, with quality, available, safe, and accurate data. She considers herself as a true data lover!


If you are part of an organization that handles large volumes of data and makes decisions with them but you are not sure what a data strategy is, what it is for, and how to start developing it, this article is for you!

I am going to tell you the main steps that will serve as a guide to implementing a Data Governance strategy that supports operational decisions for the benefit of compliance with the objectives of your organization.

  1. Define the organization’s data strategy.

First of all, let’s define the word strategy: “a general plan to achieve one or more long-term or overall objectives under conditions of uncertainty”.

Now, refining the concept, a Data Strategy would be “the plan that allows us to make the most of the knowledge we have of our data, so that the decisions we make with them are the best, accurate, on time and with the expected quality”.

It is essential to define it based on the business goals, needs, and possibilities of the organization, for example, which one will be our Data Governance framework, if we’ll have specific tools, how’ll be the structure of the area in charge of carrying out these initiatives. In short, define the “how to” work to promote and develop a “data culture” in the organization.

  1. Data Management Maturity Assessment

To develop the work plan is necessary to establish a starting point that gives us clarity and a complete picture of how the organization works with data, the pain points, and the internal and external processes that involve data from its creation to its consumption, if they compliment the expectations for which they were created, how is the security process, if it is understood what they mean, the level of confidence, if they are affected by regulations, in short, the strengths and weaknesses that the organization has with respect to its data that will allow us to identify the existing gaps and will be the driver of our project roadmap.

  1. Identify and Prioritize Use Cases

This step is one of the most important steps in the whole process and must be based on the gaps and pain pots identified in the data assessment, they are levers to generate value through the objectives set and they define where to implement the actions. Is recommended that the first use cases should be “quick wins” that will generate better visibility of the program and engagement of people in the next initiatives.

  1. Elaborate a Project Roadmap

It is an action plan with a high-level view of the tasks and deliverables to be performed throughout the project that will be elaborated based on the defined data strategy and the identified and prioritized use cases, requiring an understanding of what needs to be done and how to do it.

  1. Define KPIs

What is not defined cannot be measured. What is not measured cannot be improved. What is not improved, is always degraded.” (Lord Kelvin)

KPIs are used to synthesize information on the effectiveness and productivity of the actions carried out by the Data Governance program in order to be able to make decisions and determine those that have been most effective in meeting the objectives set in a particular process or project, and thus, to define a future course of action, correcting or maintaining the current way to work.

  1. Implement the Data Strategy

Data Governance will be finally implemented through the identified use cases, these can range from governance programs with multiple use cases, to specific projects, according to the strategy defined by the organization, having as main axes data life cycle, metadata, quality, security, and change management.

  1. Change Management

All our actions must have change management as the main driver of the operational strategy because if we do not have the commitment of people, our actions won’t be successful and won’t last over time, and this is achieved by communicating, training, and involving all members of the organization.

These actions will lead us to develop the precious Data Culture that an organization needs to make the best decisions, meet its goals, and be successful.

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