cloud bi

Self Service BI Strategy and Best Practices

Julian Alvarado

Sr. Content Marketing Manager, Sigma

Today’s organizations know that limiting business intelligence to a select few means that decisions are being made in the dark or are getting delayed until data teams can deliver necessary insights. In 2020, 62% of businesses said that self-service BI is a must for decision-making. But only about 25% of team members have access to all the data they need to make smart decisions.

Self-service data analytics has been the Holy Grail of business intelligence ever since the Big Data revolution began. But it remains elusive for many companies. This article explores the risks holding organizations back and best practices to effectively address those risks.

What is Self-Service BI?

Self-service business intelligence often gets misunderstood, so let’s first define what we mean by the term. Self-service BI describes the policies, processes, and tools that give business experts such as marketing teams, sales managers, and customer service leaders the ability to find and analyze data without relying on IT professionals or dedicated data analysts.

A plethora of “self-service” tools have appeared on the scene in the last decade, all of which have promised democratized access. But, in reality, business users are often limited to a pre-defined environment, with the ability to view only certain information via a static dashboard. If the user wants to ask follow-up questions of the data, uncover the why behind a trend, or conduct a what-if analysis, they must go back to their data engineer or SQL analyst. But data teams are incredibly busy, so it often takes hours or days to get the needed insights. Fortunately, modern analytics tools like Sigma enable true self-service analytics, simultaneously addressing security and quality.

Risks to Address in Self Service BI

A big part of the reason that “self-service” tools haven’t actually delivered self-service capabilities is the legitimate concern over the risks involved in opening up access. These concerns take three forms:

  • Data security — How can organizations prevent security breaches? What if opening access leads to compliance failures?
  • Data quality — What if business users access data that hasn’t been vetted, leading to incorrect conclusions?
  • Data education — What if business experts don’t use the necessary data logic to arrive at accurate answers? Or what if they end up relying on incomplete data?

Best Practices for a Self Service BI Strategy

These risks are real. But it’s not necessary to choose between an Ivory Tower or Wild West scenario. Implementing these best practices will address these concerns, helping you ensure you’re not compromising security or accuracy in the self-serve business intelligence process.

Choose providers with proven security in place

Almost daily, we see reports of companies experiencing the consequences of data breaches and compliance failures. No one needs to be told how important security is. While it’s impossible to one-hundred percent guarantee data security, you can dramatically reduce your vulnerability with self-service BI by taking the following steps.

At the infrastructure and application levels, you should partition virtual machines, implement access controls and permissions, use any available built-in security features, and address API security. Then look for weaknesses and implement additional tools to monitor and bolster security in these areas.

At the SaaS level, you have little to no control over security, so you must rely on your providers’ security. Therefore, it’s crucial that you examine what security measures your self-service BI provider has implemented and ask questions about ongoing security monitoring.

Look for providers that are SOC 2 compliant. SOC 2 is a voluntary program for providers who are serious about security. Because this program involves audits over time, providers must prove on an ongoing basis that they’re meeting the security policies and procedures they’ve committed to.

Additionally, your provider should comply with The Cloud Security Alliance (CSA) Cloud Controls Matrix and best practices. The organization offers a Consensus Assessments Initiative Questionnaire (CAIQ) designed to help evaluate compliance. And, of course, your provider should be compliant with any data privacy regulations that you must meet at the federal or state level, including industry regulations like the EU General Data Protection Regulation GDPR and California Consumer Privacy Act CCPA.

Create a strong-yet-flexible governance strategy

While a weak governance strategy creates security vulnerabilities and results in irrelevant data being used for decision-making, you should be just as cautious of a too-strict governance strategy. Without flexibility, business users won’t be able to get the data they need with self-service, and it won’t be scalable.

Aim for a flexible governance strategy where you can leverage your data team’s expertise without bogging down database admins and analysts. The role of data experts should be to focus on strategic projects like improving data access and providing assistance with complex inquiries that business users may not be able to handle on their own.

You’ll also want to consider policies and procedures, especially around unvetted data sources. For example, who has access to data lakes, and how can they be used? Without parameters, people will likely end up using unreliable data, leading to incorrect conclusions.

Work toward an open and collaborative data culture

Data has traditionally been the purview of data analysts and BI professionals. The idea that data should remain accessible only to professionals is often compared with healthcare — we wouldn’t hand surgeons’ tools to the financial department of a hospital to help speed patients’ access to surgery.

But unlike surgeons’ tools, today’s technology provides a safety net for business users. Business teams will still want to consult BI professionals for challenging problems or complex analyses. But by limiting business users to a dashboard, you waste their domain expertise. Democratizing access means that BI professionals can focus their expertise where it’s truly valuable. No more wasting knowledge on simple reports that could be easily handled by business teams armed with the right tools.

Additionally, BI is better with collaboration. Modern tools like Sigma facilitate collaboration without the need to share copies of data or dashboards by email. The modern pace of business combined with the power of the cloud has made real collaboration on data a corporate imperative.Companies should work toward defining and making a case for an open data culture, which will benefit everyone in the organization.

Develop an onboarding process

An effective self-service BI strategy requires a thoughtful onboarding process that equips business teams with the skills and training they need to thrive. Additionally, developing a robust onboarding process will help alleviate the concerns of those who fear opening up data access.

Teach business teams how the data platform is organized, where they can find data that’s been endorsed, what tables will be most relevant to their inquiry, and how to query data. As you’re developing your onboarding process, identify each skill that employees will need to uncover relevant, accurate answers to the questions they’ll be asking, and create training to build competency.

Sigma Workbooks for Safe and Effective Self-Service BI

Sigma Workbooks enables your business experts to find answers to complex questions and communicate confidently with data. Non-technical users can conduct their own analyses to find detailed answers in milliseconds, and cross-functional teams can easily collaborate to understand data down to a granular level and communicate their results — no need for slides, spreadsheets, or documents.

Sigma Workbooks is also ideal for data teams. It allows you to provide direct, scalable access to billions of rows of trusted data in the cloud data warehouse in real-time while maintaining security and governance. Analysts and business teams can prepare, model, and manage approved data sets quickly, without writing SQL.

See for yourself how Sigma enables safe and effective self-service BI