Why create a more data-conscious corporate culture

Data has risen to the level of a key business asset, with the speed, confidence and efficiency of business decisions increasingly rooted in data transparency and trust. To improve data transparency, data stewards (CDOs) and other stakeholders should focus on automated collection of data assets, data search and discovery, and participatory curation for data classification and description .

These features represent a lifecycle of collection, improvement, and reuse that supports enterprise-wide data insight and transparency. They can be put together and integrated using individual technologies, but most organizations prefer to use a SaaS catalog that serves as the platform to deliver these features and support a variety of user types, from non-technical to highly technical. .

“There are several best practices that should be part of a CDO’s playbook,” says John Wills, technical field manager at data governance specialist Alation. “First, the goal of creating a data culture with data transparency is one dimension of that.”

He emphasizes that this objective is a strategic initiative of the company and allows you to define the benefits in such a way as to have a positive impact on the company. “It also sets expectations for data providers and consumers,” he adds. “Second, it’s important to measure and report on business impact.”

While he admits it’s not easy, Wills says metrics that key business stakeholders will attest to are key to sustaining investment and support.

Organizations can start by capturing the “as is” state of data assets and providing search functionality. “Don’t slow down the process by starting with ‘conform’ and ‘align’ – it can come later,” says Wills. “Great value is delivered quickly by sending back to everyone what already exists.”

Finally, he notes that it is important to include data-related assets such as metric descriptions, process descriptions, terms, briefing books, and BI reports. “Connecting all of these assets brings value to a broader community of non-technical and technical users,” he says. “This is how you drive data culture – everyone participates.”

Break down silos to gain agility

Adrian Carr, CEO of Stibo Systems, explains that traditionally different types of data are managed by different departments using function-specific applications for specific business needs.

“In this kind of tech landscape, data is difficult to share and isn’t used in the same way,” he says. “Siloed data hinders business agility – it puts your data at risk of being duplicated on different systems, maintained separately and managed independently.”

He explains that data transparency depends on the availability and control of clean, accurate, consistent and up-to-date information. “Without high-quality data, even the most well-intentioned transparency initiatives are doomed to failure,” he says. “The results could be worse than this – a negative customer experience can breed uncertainty and mistrust. In this sense, it is crucial for a company to take steps towards data transparency.”

Additionally, customer experience, time to market, and competitiveness all depend on the quality and availability of a company’s data. He noted that data silos are a serious impediment to a company’s ability to operate efficiently and deliver the level of trust and customer experience that people expect.

Justin Richie, vice president of data at RevUnit, explains that many organizations struggle to break down silos, so the logic is often out of date with current business practices and will need to be adjusted. “Governance is a parallel issue to data quality, because a common bane of data silos is how data is updated,” he says. “For example, one team is looking at one type of product grouping, but another group is looking at categories in a slightly different way.”

This results in data silos as they start tracking data separately and cannot reconcile the other business logic, so everything is handled independently.

To develop a roadmap to greater data transparency, Richie says the best place to start is data governance — understanding where data inputs come from and how the data is stored, and what type of people are accessing it. what information. “Even documenting these processes can reveal potential risks to business value or even more serious security risks,” he says. “Cloud computing is an ideal way to increase adoption with increased data availability and transparency mechanisms.”

Wills points out that decision accuracy suffers when organizations have data silos because it’s unclear and unclear whether the best and most complete data is being used to represent the current state of reporting and future projections.

Secondly, considerable time is spent researching data and trying to understand if it is trustworthy, accurate and reliable each time a new question is asked – there is no reuse or retention of knowledge from the company.

“The approach to solving data silos and the challenges that come with it starts with a leadership commitment to building a data culture, which should be a valued strategic initiative,” says Wills.

Turn to data literacy, training and certification

A data culture creates standards for employee data literacy and provides open and transparent access to existing assets, as well as retention, quality, and certification standards so employees have a common understanding of data across organizations. ‘an organization. “It won’t solve silos, but it will create a transparent view of the entire enterprise data structure,” says Wills.

He adds that some of the approaches Alation has seen work well include things like providing a company-wide data literacy training and certification program, so everyone shares the same perspective, the same vocabulary and the same basic analytical skills.

Every functional business unit and area should include data training as part of their employee onboarding, as it provides a review of an organization’s authoritative data and data-related assets, the process used to maintain them and sets expectations for how employees should participate.

“Also, recognition: nothing motivates and sends a stronger message than employees seeing each other recognized and rewarded for their contributions,” says Wills. “Organizations should use mechanisms such as newsletters, awards, and leadership calls as a way to build data culture.”

Abe Gong, co-founder and CEO of Superconductive, says that to create a more data-conscious company, you need to move away from the culture of following the opinion of the highest paid person. “It’s not about reaching for the data that exists, it’s people actively trying to build the data that would allow them to answer the questions that matter to the business,” he says. “You build a supply chain to make decisions based on real data.”

From his perspective, learning about the existence of the data becomes the easy part – what’s hard is sharing the context on what the data really means. “The data is an echo of something happening out there in the real world,” he says. “To really understand the data, you often have to learn something you didn’t know about this effect in the real world.”

As data engineers are tasked with making data transparency a repeatable, sustainable, and automated process, Gong cautions against turning data transparency into a “technological priesthood.” “Business leaders and domain experts are the people who really understand where data is coming from and how it will be used,” he says. “We need them too.”

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