Self-Service Analytics

Advantages of Implementing Self-Service Analytics in Enterprise Environments

As corporate data pools continue to expand at breakneck speed, companies are scrambling to find the data engineering and analytic talent they need to transform their information into valuable insights as quickly as possible. Speed is critical in data analysis since it provides business leaders with a competitive advantage, enabling them to move quickly and achieve results. “While challenges are to be expected given the exponential growth and increasing complexity of data sets, it is not to say they cannot be effectively addressed,” says Trevor Silver, founder and leader of premier analytics, data engineering, and cloud computing solutions provider Exusia.”Data scientists and analysts already have too much on their plate, so companies are embracing self-service analytics, empowering team members across an organization to access information with ease and extract insights independently. As a result, decision-making processes are accelerated and action can be taken faster, leading to greater flexibility and competitiveness for the enterprise.”

As defined by Gartner, “Self-service analytics is a form of business intelligence (BI) in which line-of-business professionals are enabled and encouraged to perform queries and generate reports on their own, with nominal IT support. Self-service analytics is often characterized by simple-to-use BI tools with basic analytic capabilities and an underlying data model that has been simplified or scaled down for ease of understanding and straightforward data access.” According to a recent research report, the value of this market is expected to grow at a compound annual rate of 14.6% between 2020 and 2027, rising from $5.4 billion to $14 billion over the specified period. The global pandemic has categorically demonstrated the importance of adapting to market disruptions and identifying new opportunities while also managing risks more effectively, Exusia says. With remote working now a widespread option, the adoption of self-service analytic solutions allows enterprises to democratize access to data and empower all team members, regardless of their technical expertise level, to extract business insights and act quickly on them.

Given the vast amounts of corporate data that go unanalyzed and thus fail to generate any value, it is crucial for business organizations to ensure that their data is readily available for analysis to as many employees as possible, and self-service analytical tools are a key means to that end, according to Exusia. In a report focused on transforming enterprise analytic programs, Deloitte notes, “A self-service approach supports organization-wide behavior change, enabling cross-collaboration, knowledge sharing, and asset re-use. Self-serve tools have become increasingly mature and easy to use, providing drag-and-drop functionality for tasks that used to be difficult and technical, such as preparing data or developing analytical models. This further empowers business users to develop insights independently. Providing the structure for business users to develop these skills and increase their data and analytics maturity, backed by the right governance and control protocols, will be paramount for companies as they evolve their data and analytics capabilities.”

Over the past two decades, the digital transformation narrative has primarily revolved around the accumulation and analysis of data, spurring investment in tools designed to manage effectively ever-growing corporate datasets.
The business landscape in the past three decades has been shaped by the exponential build-up of data and the rise of innovative technologies that have created entire new sectors of the economy. Mobile devices and cloud-based solutions are among the most transformative developments in recent years, dramatically impacting not only consumer