More enterprises want to democratize access to internal data as much as possible. However, few companies are finding success. Capital One Software’s senior director of product management, Patrick Barch, has an idea of how organizations can succeed. 

“The most impactful business decisions are made based on insights from data. Prior to the advent of big data, business leaders might have leveraged a static set of reports and dashboards with relatively few metrics to move their business forward,” said Barch. “But the explosion of data presents an opportunity for more complex and nuanced decision making –  provided you can empower your teams with the right data.

Empowering teams with self-service access to the right data is proving elusive. According to a recent survey conducted by Forrester Consulting on behalf of Capita One Software, enterprise self-service data capabilities don’t reach much further than their data team, if they even reach there. In their survey, conducted on 150 data science and analytics decision makers across industries within North America, only a little over 40 percent of companies that plan to adopt, or already have adopted, self-service data strategies have self-service data strategies in place for their data analysts, database admins, data engineers and data scientists. 

Compare that to less than 25 percent of firms that have implemented self-service data strategies for senior business executives, data governance managers, business stakeholders such as marketing and sales, and senior business leaders. Even roles requiring data access don’t often have self-service access, with less than 30 percent of respondents saying they have such capabilities in place for business intelligence/analytics leaders, senior data leaders and data architects. 

During self-service data capabilities, essential capabilities that enable data availability throughout the organization without centralized management significantly speed decision-making — many organizations find it challenging to gain funding for their self-service programs. Fifty-one percent of respondents said they have such challenges, and the reasons have to do with difficulty linking business success with self-service data abilities and the expensive upfront costs associated with such programs. 

Interestingly, scaling data access is reportedly either challenging or very challenging for 53% of respondents. Other challenges with the same responses include maintaining user-friendly environments (49%), increasing data trust and quality (49%), and scaling self-service for decentralized environments (47%), all of which proved to be significantly reported challenges.

Barch believes meeting those challenges is worth it. “As data grows in the cloud, this is critical to operating at scale and quickly empowering all teams with insights from data,” he said. Barch contends that a self-service data strategy can transform businesses by making data more accessible, leading to increased usage and faster time to insight. “It creates more accountability for data quality, improving data discovery and building greater data trust across the organization, which allows teams to leverage more – and higher quality – data to drive business outcomes,” he said.

Establishing effective data governance is one of the foundations for making self-service data possible within organizations. “An influx of data in the cloud requires organizations to rethink how they manage and govern their data at scale. Organizations must define policies and procedures to ensure data is protected, including ownership, access, and retention policies,” Barch said.

Barch adds that as those governance policies and procedures are defined, the highest level of governance is applied to the most critical, high-value data. “Applying these policies to data housed in a central platform helps to more easily provide teams with access to well-governed data. The platform should have built-in governance so that those defining and enforcing these central policies could feel confident knowing the data will remain well managed and accessed by those who need it,” he said.

Such centralized policies can include typical data standards for metadata curation, data quality standards for shared datasets and entitlement patterns based on data sensitivity, Barch explained. “The data can be accessed through a usability layer via self-service workflows, and the consumer can feel confident knowing the data meets a set of standards defined by a central team,” he added. 

This sounds like great advice. However, regarding the secret of making a self-service data strategy successful across the enterprise? It must be considered foundational to success. “Rather than treating self-service as a separate initiative, treat it as a table stakes requirement for any data initiative that is not sought after separately.”

“To show the ROI of self-service data strategies, tie the benefits of self-service back to business success. For example, time saved from using self-service tooling, improved decision making from self-service data or reduced risk since the data is adhering to centralized governance policies via self-service workflows,” he said.

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