Why You Need a Chief Data Visualization Officer - InformationWeek

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Data Management // Big Data Analytics
10:00 AM
Pierre DeBois
Pierre DeBois

Why You Need a Chief Data Visualization Officer

A Chief Data Visualization Officer can help your analytics team tell a useful story with data and establish the right measurement framework for your organization.

Sometimes it takes a lot to get accepted. The business community today certainly accepts analytics, as well as the role of analytics practitioners, as orthodox operations essential to running an organization. It was not always so, especially when I started.

But when establishing executive leadership, there is uncertainty as to what matrix is acceptable for the business intelligence teams. If you asked pundits a few years ago, they would have said chief analytics officer is the right answer. But now, like many tech stacks, that role is not necessary the only choice.

A chief data officer (CDO) would certainly orchestrate how data can be best managed in an organization. But a chief data visualization officer (CDVO) can enhance a vision to leverage data by managing how its visualized and thus how the organization can make decisions from what they see.

The need for a CDVO stems from current analytics capability. Many web analytics solutions are no longer the only starting choice for analysis, although long-tried and trusted solutions such as Google Analytics are ubiquitous and have spawned a number of measurement options. Metrics frameworks are increasingly needed for analysts to relate dynamic data sources to KPIs and business objectives. Frameworks allow exploration into the data types being captured and the delivery of that data. Exploration of customer interest now extends well beyond a website.

That exploration also impacts visualization choices. What is the right way to show streamed data? What tools confirm that the latest data is available? Do we need tools that match professional who need are data mining but vary with skills?

The end result is that data visualization demands can cause the responsibilities of a Chief Data Officer to diverge from data collection and governance processes.

(Image: Rawpixel.com/Shutterstock)

(Image: Rawpixel.com/Shutterstock)

Addressing that divergence is critical in rethinking data management as digitalization continues to drive an omnipresent data environment. By 2020, the amount of data will increase even more. For instance, connected cars are expected to generate up to 1 terabyte of data per day by 2020. Establishing leadership that makes a CDO the only "data savior" for an organization may cause an organization to overlook new opportunities that emerge with data sources. If the organization also appoints a CDVO, that person could provide guidance on managing salient ongoing interests, such as privacy and regulation compliance.

Traditional businesses are likely encountering these kind of choices as data impacts technological decisions that are no longer confined to an IT department. In simple terms, the original objective of IT was to support a computer network. Many businesses that are just now adding cloud capability are discovering the scale of complexity that enterprise technology creates and how new concepts such as edge analytics and blockchain reveal new data concerns ranging from ETL and governance flexibility (You can read about what trends are on the horizon in Cynthia Harvey's post of 2018 Data Science Trends). These developments mean IT professionals have their attention on data storage issues that do not prioritize data consumption concerns within the enterprise. A CDVO could provide a dedicated overview of the data and BI stack with an emphasis on how the information is consumed strategically within the organization -- in essence, how data visualization informs business managers.

Another consideration involves the rising support demands from machine learning. With machine learning becoming more influential on products, services, and their supporting processes, more programmatic techniques become involved, requiring some programming knowledge to create visualizations. For example, there are various JavaScript frameworks for visualization, so creating a visual means appreciating the data being used and reviewing code to determine how to best display the data. It gets more complicated if the user is using Python or R to create an algorithm and display results. Thus, the org chart for enterprises must include someone who can recognize how a company can be best positioned with the data it has, the programming and data science experience of its teams, and the best way the information can be quickly disseminated for decision makers. A CDVO can be that person.

If data is the new oil meant to transform the future, you will need the right digital wildcatters to ensure that an organization mines in the right places. For enterprises, that leadership team takes the form of a CDO and a CDVO.

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