Establishing Data Self-Service: 4 Questions You Need to Ask

  • Kalyan Arangam, Solution Architect
  • October 29, 2019

data self service: finger touching a computer screen

Data self-service is a hot topic these days. By giving different people across an organization – technologists, marketers, business leaders, and others – access to available data and analytics tools, you empower them to make better, faster decisions. But data self-service is still a work in progress at most organizations. In the recent Matillion/IDG Research Marketpulse survey, more than half of respondents said that lines of business rely on IT or data teams to build and set up BI and analytics dashboards versus handling these tasks themselves. (Among respondents on data teams, the number who said that business users relied on IT for dashboards was 70 percent.) It’s a subject that’s on the minds of many Matillion customers.

Thinking about implementing data self-service?

Whether giving increased data access to new users or helping traditional data users achieve more advanced analytics tasks, the goal is the same: More people with agency to quickly get the information they need, without submitting a ticket or waiting in a backlog. However, moving to a more democratized data and analytics system takes strategy and planning. Therefore, it’s critical to think through your requirements and the needs of the business. Otherwise, you can risk several challenges: to security, data access, and usability, to name a few.

4 Questions you need to ask about data self-service

Before your organization moves forward with a data self-service initiative, there are several questions you should ask. Considering these questions up front will help you develop a comprehensive plan that is more likely to succeed and benefit your end users.

1. Where is your organization now, and where is it going?

You need to understand where the company is at present – organizationally, technology-wise, in terms of the market, and more. Where do you want to be? And what are the challenges standing in the way?  For example, you may be generating masses of data. But merely having access to it all may not be all that useful. It’s important to define what business questions need answering and how data can help you get there.

2. What does data self-service really mean to your organization?

Clearly define what self-service means for each user or role who needs access to your company’s data. What’s needed for day-to-day reporting? What’s needed to strategize and innovate? How do you handle ad-hoc reporting? And what about plans to use artificial intelligence and machine learning in the future?

3. What about security and data governance?

This is a burning question for many organizations looking at data self-service in the cloud, or even not in the cloud: How do you allow multiple users to access data without compromising systems or security?

You may already have data management and data governance strategies in place. How does moving to the cloud affect these policies? Are there further regulations that apply when moving to the cloud? How does self-service play into your overall cloud security strategy?

It’s important to focus on data governance as a practice. Establishing the right auditing measures and necessary controls provides users with data access. But it also allows IT to gain the transparency it needs to understand who uses what data.

Moving to the cloud may introduce new measures to help users access to resources in the cloud. For example, many organizations prefer to implement MFA besides username/password for user login. Identify what’s right for you.

4. What are the blockers you might face?

You may have tried data self-service before, and not been successful. Identify the challenges you faced or continue to face. Were they barriers associated with an on-premises solution?

Cloud, by default, often helps overcome technology-related challenges and eliminate past issues. Most cloud providers and data platforms provide additional tools to manage people, processes, and access to relevant resources. These tools can eliminate possible objections and blockers to implementation of data self-service. There may be hurdles that a cloud platform may not resolve, such as human resources and marketplace challenges. Consider these as well.

Implementing data self-service is a multi-step process with many choices to make. But if you start by asking the right questions and creating a plan, you’re on your way to creating a solution that works for both IT and business users in your organization.

Learn about how Matillion can help transform your data in the cloud and prepare it for analytics. Get a demo today.