Understanding the synergy between Augmented Analytics, Decision Intelligence, and Gen AI

Reading Time: 2 minutes

As we delve into the current state of the analytics industry, one cannot overlook the transformative power of Augmented Analytics. Gartner’s description of Augmented Analytics involves leveraging advanced technologies like Machine Learning and Artificial Intelligence to aid in data preparation, the generation of insights, and the explanation of those insights. This approach enhances the way individuals explore and analyze data within analytics and business intelligence (BI) platforms. This approach not only empowers data analysts, but also enables all business users to harness the full potential of data without requiring advanced technical skills.

Decision Intelligence, a closely related field, focuses on leveraging data and analytics to optimize decision-making processes. This synergy between Augmented Analytics and Decision Intelligence is reshaping the way businesses operate, providing them with a competitive edge in the data-driven era.

Fosfor has been a key player in the space with its Decision Intelligence product, Lumin. And, we are thrilled to announce that for the third consecutive year, Lumin has been recognized as a representative vendor in the 2023 Gartner Market Guide for Augmented Analytics! This acknowledgment reaffirms our commitment to empowering businesses with the tools they need to thrive in this data-centric era.

Augmented Analytics and Decision Intelligence disrupted by Generative AI

Augmented analytics leverages Machine Learning and AI to enhance the data analytics processes. It automates insights generation, data preparation, and even suggests actions to be taken, making it possible for a broader range of users to make data-driven decisions, and not just data scientists. In recent times, Generative AI (GenAI) has evolved as a strong enabler and catalyst for Augmented Analytics as well as Decision Intelligence. This Gartner market guide speaks to the momentous impact Generative AI will have in this space, as well the expected increase in analytics assets, and the ease of adoption.

Large Language Models (LLMs), like GPT, have ushered in a new era of decision-making by enhancing Natural Language Understanding (NLU), predictive analytics, and contextual reasoning. They possess the unique ability to decipher human language intricacies, context, and intent at an unprecedented scale.

Here are a few ways in which Generative AI is revolutionizing this space:

  • Augment AI training data sets – Gen AI is being used to generate new data points that can be used to improve the accuracy and reliability of Augmented Analytics models. This can be particularly useful when real data is scarce or difficult to obtain.
  • Enrich text analysis – LLMs are particularly adept at quickly processing large amounts of text and extracting key insights. This is achieved through Natural Language Processing (NLP) techniques, which when used in combination with any Decision Intelligence tool, can be incredibly useful in a variety of industries, from Finance to Healthcare.
  • Enhance contextual learning – GenAI models are also being used to understand user context, queries, and behavior better. The complex AI model responses or recommendations generated by Decision Intelligence tools are also being simplified using GenAI technologies to understand and interpret the reasoning behind them.
  • Improve interactivity – Since GenAI can generate more human-like natural language responses created by Natural Language Processing models, this makes user interaction and communication with Augmented Analytics tools much easier. This can save a significant amount of time and resources for businesses. For example, GenAI can be used to generate a range of items such as customer service responses or news articles, freeing up time for human writers to focus on more creative tasks.

Flow, our latest Gen AI integration in Lumin, leverages all the above use cases to enhance and improve the insight generation process as well as increase the overall analytics adoption in enterprises. Lumin’s Gen AI integration leverages LLMs to understand queries, remember interactions, and provide contextually relevant responses, empowering users to explore data interactively and uncover deeper insights and patterns that may have been missed with traditional querying methods.

Conclusion

As businesses navigate the complexities of the modern marketplace, the ability to make informed decisions swiftly and accurately is a defining factor for success. Lumin’s recognition in Gartner’s 2023 Market Guide for Augmented Analytics is a testament to our commitment to providing a best-in-class Augmented Analytics and Decision Intelligence solution.

The guide also highlights the growing trend of cloud-first Augmented Analytics solutions that are now becoming the new norm in this highly competitive marketplace. Lumin’s cloud-native connectors and domain-rich solutions in partnership with hyperscalers such as Snowflake and Databricks, as well as the availability of ready-to-deploy solutions and use cases on public cloud platforms like AWS, make it a clear winner in the Augmented Analytics and Decision Intelligence market.

By embracing Lumin, you are not just adopting a tool; you are embracing a transformative approach to analytics that will position your organization as a leader in the data-driven revolution. Stay ahead of the curve, unlock the full potential of your data, and make decisions that propel your business into the future with Lumin.

Author

Ankita Asthana

Product Marketing Manager, Lumin by Fosfor

Known as a creative individual, Ankita has a knack for thinking out of the box. She is known for creating compelling stories and use cases around products to generate interest and create long lasting impressions for the audience. In her current role, she enjoys bringing Lumin- an augmented analytics product, part of Fosfor suite, to life in fun and captivating ways.

A founding member and advocate of Product Marketing Alliance (PMA), Ankita has dabbled in brand and digital marketing and loves to hone her storytelling skills in her free time

Latest Blogs

See how your peers leverage Fosfor + Snowflake to create the value they want consistently.

Data-driven Signals on Lumin

We are often troubled by incessant notifications that disturb us on social media platforms. They take our attention and focus away, and the amount of time we lose due to these pesky chimers is countless. But what if we had the power to easily define what friends/communities we would like to keep a tab on? What if we could tell social media to notify us only if we had to know? Interestingly enough, decision-makers and data enthusiasts struggle with this problem too.

Read more

Making your Snowflake pipeline robust with Fosfor Spectra

"How can I avoid constantly jumping between Snowflake UI and Spectra UI to know what transformations would be apt for this data pipeline I am trying to configure on Fosfor Spectra?" 

Read more

Technical debt in machine learning

Technical debt refers to the cost of any shortcuts or sub-optimal solutions taken in the development process that can result in difficulties and increased costs in future maintenance and software upgrades. The term "technical debt" was coined by Ward Cunningham in 1992.

Read more