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For as long as we’ve known, the world has been in a constant state of flux. New possibilities emerge whenever new technologies are born from old ones. This was true when vinyl records made way for iPods, which made way for digital music. Or when goal-line technology put an end to debates about refereeing errors in soccer – giving rise to, of course, fresh debates about the technology itself. What started as ‘Data Warehouse’ in the 2000s has today grown into an analytics universe, spanning data lakes, data governance, visualization, and more. At Spoggle, we believe we’re a crucial addition to this expanding ecosystem.
It’s anyone’s guess where our story begins. Let’s turn the clock back by a decade. Arriving hot on the heels of big data’s entry in 2010, data analytics was quickly gaining ground through Hadoop and Apache Spark. These products revolutionized how large data sets were processed. Thanks to them, data stored in stray locations could be accessed to create data models that yield insights.
Working as our founders did at the time in companies like Capgemini, CSC, and Covansys, they witnessed firsthand the chinks in the analytics armor. In its early stages, the journey from data to insights was not as simple. In this process,
data would be gathered based on business requirements from various sources,
models would be built, accounting for relevant customer and product information,
and reports would be generated to communicate insights generated from this data.
However, integrating any extra data that arose from new business requirements was cumbersome. A small change in the dataset would mean that the entire cycle had to be repeated, stealing effort and time from users.
But what is technological evolution if not building new technologies using existing ones? Over time, parallel data processing emerged as a savior, and teams could work independently to access and analyze data from various sources. Cloud storage became more affordable, and platforms like SAP and Salesforce threw open the doors to customer data from various sources. Data lakes became a popular data storage system where users could perform data processing operations.
Despite this, a notable gap persists: the team possessing data access and processing capabilities differs from those urgently requiring actionable insights, such as CEOs, COOs, and other decision-makers. This disconnect hinders decision-makers from freely exploring data and understanding how various parameters impact executive decisions. Even when equipped with data access, decision-makers often find themselves juggling multiple tools to generate meaningful reports. Addressing this void in the analytics lifecycle becomes crucial.
Spoggle is an analytics ecosystem specifically designed to bridge this gap. Here, decision-makers gain access to the data lake and perform data processing tasks with simplicity and intuitiveness. With AI-powered self-serve tools like Ask Spoggle, executives can explore and visualize data on their own, making informed decisions faster.
Spoggle’s objective is twofold: first, to make actionable insights readily available to every business user, and second, to provide a unified platform encompassing all analytics tools within reach of the decision-making tier. Plus, Spoggle's versatile user base spans individuals skilled in basic analytics seeking self-serve analysis, business analysts playing a pivotal role in delivering extensive analytics support to decision-makers, and citizen data scientists.
In other words, the idea at the heart of Spoggle is to eliminate barriers between data and insights. The bridging of this barrier means that business users can work independently with data, reducing their dependence on IT teams. This comes with quicker time to market, and reduced digital friction, removing the unnecessary effort spent on technology that could be redirected to high-priority tasks. Spoggle simply captures the philosophy of ‘a single pane of glass’: quickly giving users the big picture and the tools to dig deeper, all in one place.
Today, Spoggle is the bridge that connects IT teams and business users. From day one, we’ve looked for ways to make our product user-friendly – in fact, our self-serve platform was built with the intention of making analytics accessible, even for those without technical know-how. We’re slowly but surely realizing our idea to reduce time, effort, and more importantly – costs. While most analytics operations today require investment in several tools, Spoggle is an end-to-end solution for every analytics requirement.
As technology evolves at breakneck speed, Spoggle’s vision is to keep pace with the times. And our favorite way to grow is with our users.
