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A CIO forges a data strategy plan for creating actionable data
As CIO of Data Conversion Laboratory, Tammy Bilitzky is responsible for the technology that her organization and its clients need to turn content into actionable data.
Tammy Bilitzky's job is all about actionable data. Bilitzky is CIO at Data Conversion Laboratory, which organizes,...
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converts and moves content for its client organizations. As CIO, Bilitzky is responsible for the technology that DCL uses for its own internal business needs as well as for the IT required to process customers' requirements.
That has given Bilitzky a broad view of organizational data needs, strategies and challenges.
"There is no industry that isn't powered by data and doesn't need data to move forward, so companies understand the criticality of a data strategy today," she said.
However, she said organizations continue to struggle with knowing what's valuable in the vast amounts of content they have and formatting that valuable content into actionable data and information.
In part one of this two-part Q&A, Bilitzky discusses how her technology strategy supports DCL, its work with client data and what her job has taught her about data strategy.
Editor's note: The following has been edited for clarity and length.
How does your company approach its work?
Tammy Bilitzky: Our goal is to take content, which could be unstructured or free-form, and turn it into actionable data. Content by itself doesn't have meaning, because you don't understand the context. Data is when you're lending meaning to it. So we're taking pure content and transforming into something that's usable, data that companies can take action on.
So many companies have content; they almost have too much of it. The challenge is working with them to understand the content they have, what they need and what's not relevant right now.
Why should companies differentiate between content that's relevant now vs. at other times?
Bilitzky: Information that you don't think is relevant right now can change in value. So wherever we can put a hook to preserve information for the future, we'll do that. Even if we don't take all the content and turn it into actionable data, we may take that data and leave it unstructured. We always like to leave that door open if there's information that the client has but can't think of a business case to use right now.
Do you distinguish between content, data and information?
Bilitzky: My definition of content is it's not in the precise format you need. It might not be structured enough or doesn't have the semantic analysis or the context you need. For example, you have a number, but what does that number represent? Or if someone says something's 'bad,' what does that mean? In today's day and age, the word 'bad' could mean good or bad. You need to look at the context to determine if it's being used in a positive or a negative way. That's why I talk about applying context to content to turn it into actionable data.
Information to me has to be informative. People use information to talk about content and data, but I wouldn't call raw data information. Raw data is not informative. There has to be context to add to that data to become what I consider information. There are data points. For example, this person weighs this amount, this person is this height. That's data, but you need other pieces of data around it to make it useful.
You've talked about the concept of triples as a way to make data useful. What is that?
Bilitzky: It's a way of representing information -- subject, predicate, object. You start with metadata: You pull the information out about the data you're working with. Say I'm working with a journal article, so who is the author? What college did the author go to? That's just raw data. Now you want to relate that to other data. You have this author who attended this university and got this degree. Now you have not just three pieces of data, you have three related pieces of information that give you much more context. And it just keeps going. Today you need to be able to take the data to a completely different level than you did in the past. This allows you to apply filters to the data.
What are your top priorities as CIO?
Bilitzky: My priorities are really developing my resources. We're making sure people know the value of what we're delivering and the need to deliver high-quality results. To facilitate that we spend a lot of time on best practices and making sure we're being consistent. Communication is a key part of that work. People work on a lot of key projects, and there's an overlap in their work. But we don't want to [duplicate work], so we spend a lot of time on sharing information so no one is reinventing the wheel.
As a CIO, you also have to make sure your strategic goals are there and that you know what your staff is focused on so you can stay aligned with those goals. But you have to have a balance between your strategic goals and the tactical needs, too.
What are your top challenges as a CIO today?
Bilitzky: Everything I just said on the flip side: Keeping aligned with the business is the biggest challenge that CIOs have today, making sure everyone is communicating effectively and continually making sure that the projects we're working on are the ones that reap the most benefits.
What are your strategies for bringing AI and related technologies into your organization?
Bilitzky: The barriers of entry for machine learning and artificial intelligence and natural language processing have dropped, [but] there are still barriers. To leverage these technologies, there's a lot of specialization needed. We've been developing some of our team, helping them to learn these new technologies. And we're working on partnerships with companies that have that expertise so we can deliver value to clients. The key is understanding what the clients' needs are and putting together a product that will deliver on those. But we don't need to build what we can buy. We want to build what no one else has.