Self service analytics

Large organizations typically have dedicated data science and analytics teams that help different business departments to answer their data related questions. Although wides-spread this division of work has two significant shortcomings:

• First, naturally a central team will have limited resources. As requests for work from the business often exceed the team's capacity this results in a bottleneck and delays.
• Second, the central data teams often times lack the detailed domain knowledge and context to perform their work in the best way possible. Further delays and backs and forths until the desired outcomes are achieved are the consequence.

Enter self service analytics.The idea is simple: to empower the business units themselves - virtually anyone - to get to data driven answers for their questions. This has been a desired concept for many years. However, it largely remained theory. And there are two reasons for this:

• Lack in data literacy: Many individuals in organizations are not used to working with data. And by that we don't mean training sophisticated machine learning models. No, even descriptive analytics in Excel is just not something everyone knows how to do. This is of course a natural barrier to the self-service idea.
• Concerns around data privacy: Even if the data literacy is there, the other big challenge is data governance. For good reason not everyone in an organization gets access to every dataset. The more individuals have access to sensitive data, to higher the risk of a breach or incident happening. But of course - without access to data, self-service analytics remains a theoretical concept.

With the introduction of privacy preserving synthetic data and powerful Large Language Models this theory now becomes reality.

The MOSTLY AI Platform addresses all of the previously mentioned challenges when it comes to self service analytics.

• The possibility to grant granular data access to everyone is ensured through privacy-preserving synthetic data
• Everyone is enabled to generate insights from that data through the LLM powered Assistant

While self service analytics may sound like a dream come to true for some, it may sound like a nightmare to others. Will this mean fewer jobs for data scientists? Will business owners be now left all by themselves to answer their most pressing questions? Quite the contrary is true. Self service analytics is a win-win situation for everyone and there are multiple benefits.

• Reduced time to insights: The business functions will get answers to their questions faster. One because they can now answer many questions themselves, two because the back-log of the data science and analytics team is much shorter.
• Higher quality analyses as the data teams are freed up to do more of the sophisticated work: Of course data analysts and data scientists are still needed. But they can now focus their time on the really difficult challenges as the simpler questions will be self-answered.
• Eventually this leads to better informed business decisions: Everyone probably agrees that decisions should be informed by data. But still today often times the gut feeling is more relied upon than data. Self service analytics changes that once and for all increasing the quality of business decisions and thus helping companies overall to be more successful.
• Increased data literacy among everyone: The more you work with data, the less intimidating it becomes. LLM powered self service analytics not only gives you answers, but it's also very patient and willing to explain everything in detail.

Self service analytics driven by access and insights to data is the ultimate driver for true data democratization!