Self-Service Data Without Chaos

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Read more about author Diby Malakar.

Information is power, and the ability to put information into the hands of those who can quickly act on it separates the leaders from the laggards in any market. Everyone in an organization – from HR professionals leveraging data to dictate hiring decisions to brand managers leveraging data for pricing optimization – benefits from analytics. However, the need to understand SQL, database structures, and the theory behind joining tables impedes non-technical users from finding, understanding, and using data for decision-making. Self-service data analytics empowers business users not trained in Data Science to quickly discover trusted data, fostering greater operational efficiency and eliminating bottlenecks. 

While this idea of “democratizing data” through self-service sounds ideal, putting it into practice is another story altogether. Ventana Research reports that half or less of the workforce uses analytics in three-quarters of organizations. There remains a reluctance – or even a fear – among leaders to adopt self-service data initiatives, with many in Data Management roles worried that it means a free-for-all that compromises data security and could bring compliance into question. For many of these folks, the sustainable business model they’ve helped build is the result of managing risk by locking down the data they have and doling it out judiciously and only on an as-needed basis. They’re not wrong: Enterprise data in the wrong hands can be a security and regulatory nightmare. But just as nightmarish is overlooking the innovation and growth that can be realized when data is accessible on demand to all authorized users.

To drive a data culture on top of an active metadata platform, data needs to be engaged with and adopted by everyone; it also must connect to everything. Furthermore, the metadata platform should be open and extensible. 

Balancing Self-Service with Transparency, Trust, and Security 

Discomfort with providing self-service access to data inhibits innovation within organizations but fears about giving business users access to data are valid: Will bad actors compromise security? And, will good actors become bad actors when they unwittingly violate regulations because the data they now have access to is too confusing and overwhelming?

Overcoming these concerns and moving forward with true self-service requires a three-pillar approach, always with transparency and trust in mind: “transparency,” in terms of providing regulations and rules around how to use the data; and “trust” in terms of not only giving up control for the benefit of the company’s growth but ensuring that the “democratized data” is universally trusted data. 

  • The first pillar required to enable this environment is a self-service analytics platform, where individual business users are empowered to find and use the data they need on their own and without the help of a Data Science team. Users are looking to find easier ways to understand the lineage of data at the level of detail that is suited for each type of user. 
  • The second pillar is cloud transformation. Cloud-based systems improve access to data, allow real-time collaboration and communication, and enhance analytics by eliminating data silos. 
  • The final pillar is a federated approach to Data Governance, which clearly defines how data should be gathered and used in an organization. Data Governance ensures all business users understand and abide by the rules of engagement to reduce the likelihood of data falling to misuse. 

Many companies are also adopting Data Governance teams – a trend that has taken hold over the past year. In fact, Forrester predicts 2023 will bring 30% growth in the number of companies with a formal Data Governance team in place. These teams support an insights-driven organization, using provenance, lineage, quality, privacy, and security principles to underpin Data Governance. 

Shifting the Business Culture to One of Self-Service

For those trained to keep data locked down for the good of the company, giving up control may be uncomfortable. However, once you’ve ensured security won’t be compromised and trusted data is available, fostering a data culture is the next objective that is critical for enabling self-service within your organization. This means non-technical users must undergo a culture shift that will change how they do their jobs. Standardizing language and terminology is central to this shift. Aligning disparate departments on key terms creates shared understanding so that data is used consistently and appropriately and that users can make more data-informed decisions faster than ever. 

Empowering the non-technical end user with self-service data will become critical to survival in 2023, and balancing it with compliance, security, and data culture will be equally important. It is all about making it easy for everyone to find, understand, and trust data and about enabling everyone to use data the right way and maintain compliance. With data recognized as any company’s lifeblood, those prioritizing data democratization through self-service data will set the stage for success now and into the future.