Affiliated with:

Merill Albert

Merrill Albert

Enterprise Data Leader, Data Governance Officer, Data Thought Leader, Chief Data Officer

Ms. Albert is a lifelong data person with a combination of industry and consulting experience.  She knows both theory and how to apply it and has lived data problems and knows how to solve them. 

Ms. Albert believes in understanding the business needs to solve the problem, keeping a tool-agnostic view and is passionate about companies having the right high-quality data, used compliantly, to make appropriate and timely decisions.  She helps companies better manage their data to drive value from it.

What attracted you to data management or IT, and why did you choose to pursue this career?

You could say I was born this way.  Organization is good in life and data.  I have a very specialized degree (BMath majoring in Operations Research with a Computer Science minor), which is where the professional focus began.  As the data management space has evolved, I have had people look to me when some new buzzword comes out with “data” in it.

What has been your greatest career accomplishment so far, and why has it been important to your career?

I am proud that my entire career has been a focus on data, although in different roles.  I have built data models people have deemed “sophisticated” and flexible to grow with the business.  I have worked places where I created my “magnum opus” of everything I know so far in data management to help train people.  I have played the role of a CDO in managing all the company’s data.  I have worked as a consultant where I have helped clients develop their own data management practice.  It is rewarding when they reach that “ah-ha” moment and finally understand how not properly managing their data has been negatively impacting their business.

A fun thing is that I came up with the hashtag #CrimesAgainstData.  You will often see my posts on LinkedIn about data crimes.  Someone suggested that these are crimes against me using data, which is somewhat true, but they are not always personal.  The point is helping people see the problems that can happen when there is an issue with the data.

What are the two or three biggest challenges you face as a data management professional / CDO and how can we address them?

I think the biggest thing people keep forgetting is that data management needs to be business-led and technology-supported.  A new tool might be sparkly, but you still need to give it the right data, understand the rules around the data, and make sure people do not misuse the data.  We did these things before the fancy tools came along.

As people anticipate what data science can do for them, they often forget the basics.  We still need the right data.  I see data as an industry in and of itself where we can apply the same data principles to all “traditional” industries.

How do you see data management / the role of the CDO / IT changing in the next 2 – 3 years?

I like to think we learned a lot in 2020.  We saw data on the news every night.  We noticed when the data seemed to be misrepresented.  We learned about discrimination and bias in data.  I like to think we will take these ideas forward and better utilize data in the future.  However, the reality is that we will probably still struggle with people who do not understand the dangers of bad data and think it will just magically be right when they need it.  No matter what, it always comes back to the data.

Do you have any planned next steps for your career?

I have spent a career in data and plan to continue being that Defender of Data.

What is the single best piece of advice you have received in your data management / IT career so far?  Why has it been so important to you?

Hope for the best; prepare for the worst.  It is not really the optimistic view or the pessimistic view, but the realistic view.

Can you share something about yourself as a person that people wouldn’t know about you?

I am highly creative in different mediums.  I love to travel.  I am also the family genealogist, which is why you often hear me refer to data lineage as data genealogy.

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