Unlocking the Potential of Associative Analytics

Earlier this month, InsideAnalysis hosted Aaron Wilson of Athena Solutions and Jim Smith of Qlik to discuss the journey many businesses are making towards a deeper, more intuitive understanding of data. Much of this transformation is fueled by the principles of associative analytics: By harnessing and even mirroring the brain’s natural ability to make connections, we can interact with data in more authentic ways, making the analysis process not only more efficient but also more insightful.

Communicating directly with our data hasn’t always been easy. Wilson explained, “The downside to query-based filtering is that you lose the contextual data that doesn’t apply to your filter, but with associative analytics, you don’t lose the forest for the trees.” The essence of associative analytics involves including the broader context that surrounds our data, even as we delve into the stories that specific data points tell.??

The Power of Exploration

For many users, the true value of data analytics lies in the freedom to explore. Traditional analytics often confine us to predefined paths. Following such a script limits our ability to uncover unexpected insights. Associative analytics allows users to deviate from that narrow path, providing a more open-ended approach to data exploration.

Wilson emphasized this point: “For a user, once they get their hands on the data tools, the next thing they want to do is explore it.” Introducing an associative approach to analytics at the get-go of a project allows users to deploy their curiosity and improvise in real-time.? If a data point exists that is more compelling than what is offered on the prescribed path through an environment, users can feel empowered to switch their trajectories.??

Speed and Agility Through In-Memory Architecture

The backbone of this transformative approach to analytics is an in-memory architecture. By storing data in-memory rather than on disk, associative analytics systems can respond to user queries on demand. Users can navigate their environments fluidly without facing the interruptions caused by slow processing times.

“When that data is in-memory and you start to slice and dice it as an end user, you don’t want?

to see a bunch of progress indicators telling you to wait five minutes as it pools through resources,” explained Smith, “Qlik offers immediate access to the information you asked for.”?

In addition to improving the flow of users’ experiences, the in-memory architecture also increases their flexibility. As users interact with their data, the system can quickly recalculate and update visualizations, ensuring that the most relevant and current information is always available. This agility is particularly valuable in fast-paced business environments, where timely insights are essential for staying ahead of the competition.

Diversity of Data

In addition to user experience, associative analytics can have a profound impact on actual data quality. Associative analytics allows for a wide range of sources and structures that can enhance a project’s accuracy and scope. Traditional analytics systems often struggle with data silos and incompatibilities between different data formats, which can impede how representative one’s data is. Associative analytics breaks down these barriers, providing a more comprehensive view of the data landscape.

This holistic approach to data analysis not only enhances the depth and breadth of analysis but also ensures that no critical piece of information is overlooked. “Most traditional analytics models only process structured data,” explained Eric Kavanagh , host of Inside Analysis. “What’s so interesting about these large language models is that they work with unstructured data.” Opening up the criteria of data sources to include PowerPoint presentations, chat histories and other interactions that include valuable information increases the likelihood that a complete story will be told through data.?

Optimizing Discovery and Preserving Data Governance

The challenge of balancing discovery with data governance is a key consideration for any project, including those by organizations adopting associative analytics. Though users are encouraged to lean into their explorative natures, data integrity and security must be monitored to accommodate this flexibility.??

David Linthicum, another expert on the show, had some insights on how to monitor and correct what is wrong: “Most enterprises are not utilizing their data in the correct way where they’re able to find insights into what is incorrect, Linthicum said. “With everything being transaction oriented, they can’t see what is wrong with their business based on the way they are tracking information.”?

Kavanagh added that data literacy plays a vital role in collaborations between and within businesses. “Don’t just use data for your own personal consumption. Use it to start conversations and ask people about things because that fuels analysis and enables data governance.”?

Qlik’s Associative Engine and Athena’s Data Analysis Sandbox?

Athena Solutions and Qlik both have their own tools that are designed to handle the complexities of modern data environments, providing users with intuitive tools for exploring and analyzing data.

Data Analysis Sandbox brings in a semantic layer on top of all the different types of data sources and allows the user to do an explorative process. “Once you give people the power to get their hands on data, it’s a short hop from their to wanting to produce real analysis,” said Wilson.?

Qlik’s Associative Engine similarly reveals key relationships within diverse data sets, fast-tracking the analysis process. “You still have executives that don’t want to do any slicing and dicing. They just want to get their dashboard and don’t want to go to a separate tool,” said Smith. Qlik wants to encourage end users to accept the variety of avenues that are available to them. Smith explained that “visualizations are great but you have to get the right data to the right person in the right format.”?

Conclusion

In a world where data is both abundant and essential, the ability to explore and analyze it without constraints is invaluable. Associative analytics provides this capability, enabling users to traverse complex data landscapes quickly and efficiently. By preserving context, facilitating dynamic calculations, and integrating diverse data sources, this approach offers a comprehensive and agile solution for modern data analytics.

Learning from industry experts on how to put associative analytics into play can transform your organization’s data analysis processes. The future of data exploration is here, and it promises to unlock new pathways to insight and innovation.

Listen to the full webinar here => https://youtu.be/9-bs6RyaUXo