APEC Data Science & Analytics Key Competency #3: Data Management and Governance

According to the APEC (Asia Pacific Economic Cooperation) Advisory Group, Data Management and Governance is one of the key competencies of a Data Science & Analytics professional working in the region.

By definition, a DSA professional can develop and implement data management strategies and governance, while incorporating privacy, data security, polices and regulations, and ethical considerations.

The concepts of data management and data governance are kind of the like the chicken… you really can’t have one without the other. Although to the layman, data management includes data governance.

The simplest way to put it, is that data management is the physical aspects of data collecting, capturing, storing, segmenting, etc. Data governance is then the rules or guiding principles that direct how data management works.

There are a lot of data management resources out there. There are not a lot of data governance resources out there. This is why in a majority of companies, we have raw data that needs a lot of cleaning and refining before it can be used in a business.

Organizations that are good in data governance, generally have solid data management. Mature analytics companies have data that is easy to access, is accurate and is used in decision-making.

Data Governance is composed on three parts: People, Process and Technology.

DMAI_DataGovernanceThe people have titles like database admins, data stewards and data warehouse experts. They enforce the laws and rules around data within an organization.

The technology used is generally programming languages, coding and joining data structures to layout the blueprint of how data flows throughout the organization’s hardware.

The process is the rules, generally set down by senior management, and often in line with government or industry regulations that govern how data should be used.

If your organization has a lot of data, has people that are well versed in data management, and uses data to feed decision-making, then you need to make sure you have solid data governance.

If you don’t, DMAIPH can help. Likely you are missing key people, clear processes, and/or the right technology to ensure your data is being governed correctly.


Analytics Training – DMAIPH offers a wide range of analytics centric training solutions for professionals and students via public, in-house, on-site, and academic settings. We tailor each training event to meet the unique needs of the audience.

If you need empowerment and skills enhancement to optimize the use of analytics in your organization, we are here to help. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation to learn which of our DMAIPH analytics training solutions is best for you.

Chief Data Officer – The Data Geek in the Room

In his latest book Data Strategy, analytics guru Bernard Marr, discusses how to profit from a world of big data, analytics and the internet of things. Marr breaks down the importance of having a data strategy to ensure data-driven decision-making, improve business operations and to monetize the data in a business.

data strategy

One of the key takeaways from his book is the emerging role of Chief Data Officer. This is a separate C-Level Suite position form the more traditional Chief Technology Officer or Chief Information Officer as this person should serve as both an analytics cheerleader and data-driven decision-making champion.

Big companies have CDOs, but even smaller and medium sized companies need to have someone who acts in this role even if its not an official title. I often say that analysts have to not only analyze data, but be champions of using data for decision-making. They have to be the data cheerleaders to educate, enable, and empower the use of data and analytics across the organization.

There are six primary areas a CDO should oversee; (1) high level vision, (2) implementations, (3) data governance, (4) business opportunities, (5) data culture leader and (6) sees data as a commodity.

  1. CDOs have to have either a seat at the C-Suite table or the ear of the top decision-maker in the company. They are the ones who make sure that data is properly channeled to the right people at the right time to ensure data-driven strategies.
  2. CDOs have to be the one ultimately responsible for data project implementations. This is not an IT thing. IT should be involved, but not the owners of data and analytics.
  3. CDO’s have to make sure good data governance is followed. Data has to be stored, secure and accurate.
  4. CDO’s are the ones who have the task of discovering business opportunities and identifying risks. They should have access to all the data they need to do both.
  5. CDO’s are the ones who consistently and clearly articulate the importance of data and the value of data-driven decision-making.
  6. CDO’s see data for its monetary value. Data is a commodity that in itself can be used to not just help the company, but to generate revenue itself.

So if you have a Chief Data Officer, or just a chief data geek, you are on the right path. If you don’t have one of these in your organization then your organization are likely going to be left behind.

may 17-18Analytics Culture – The key to using analytics in a business is like a secret sauce that fuels Data-Driven Decison-Making. It is a unique combination of analytics talent, technology and technique that are brought together to enrich and empower an organization. A successful analytics culture is not easy to create, but DMAIPH can show you how. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can build a strategic plan to turn your company into analytics driven success story.