AI for data analytics: Automating reporting & insights

For most business owners – big and small – the number one thing that stands in their way is understanding what’s going on with their data. Up until now, data has been represented in ways that are unnatural to us as humans. We’ve been forced to interface with dashboards, reports, and screeds of breakdowns that are not intuitive to someone who doesn’t have a background in data.

This obscures the trends and patterns that could be helping you grow and improve your business! AI for data analytics changes that.

AI business analytics and automated insights, like the kind we offer at SyncHub, let you interface with your data in the most natural way possible: through conversation. You chat with an AI agent immersed in your business’s data, no BI or SQL necessary, and it produces the most up-to-date data in easily interpretable ways.

This is a new way of working, but a powerful one. So, what are the benefits of working with AI analytics to automate how you process your business data? Let’s find out.

Zero technical friction

Every single person in your business – including you – should be able to access and understand the backend data relating to your business performance, if you so choose. Most of the time, creating this kind of data visibility requires a ton of waiting. You have to draft internal tickets for your BI developer, or learn complex SQL to write queries for yourself.

If someone doesn’t have the right technical syntax, then the data is simply closed to them.

If someone doesn’t have the right technical syntax, then the data is simply closed to them. Or, if they try to use multiple different platforms to understand visualised data, they’re still getting a disparate picture from the perspective of multiple different systems (i.e. financial, sales, CRM, etc.) There’s no whole picture easily available.

This is why AI for data analytics is so powerful. AI analytics removes that technical wall completely, so you can have a conversation with your data instead of communicating via code. You can ask questions the same way you might speak to a human colleague and receive high-fidelity, clear answers from your AI business analytics engine that don’t compromise the data itself.

Zero technical friction means everyone can move faster and make better decisions. It’s that simple!

See things visually, quickly

Human brains aren’t evolved to interpret massive grids of numbers and cells. Picking out major spikes in operating costs or big, visible dips in sales is possible with the right time and dedication, but more often than not, our instinct as humans is to visualise this data. This is why businesses have often relied on their financial, sales, and inventory departments to produce long visualised reports at specific intervals.

With SaaS models jumping in popularity over the last few decades, that shifted to visualised data on the backend of different tools. But the problem is, those pieces of data exist in silos. When you try to parse them together, vital relationships are easy to miss, especially since combining the raw data often takes away the ability to visualise it easily.

This is why an intelligent AI analytics assistant was so important for us to create. With your combined data at its fingertips, your assistant can instantly pull data relevant to your query and visualise it based on the relationship you are interested in. It’s a dynamic, fluid approach that adapts to what you need each day.

Track audit trails for transparency

One of the biggest concerns you might be running into with your business right now is the idea of the ‘black box’. Automated insights are amazing, but if you can’t see how the AI business analytics engine arrived at that answer, how can you be sure it’s correct? How can you be sure it didn’t just hallucinate the number out of thin air?

We solve this by creating transparency trails for human quality assurance. There is absolute accountability baked into the AI business analytics engine, including:

• Visible SQL queries to demonstrate how the data was gathered
• Database tracking to show where and how your AI for data analytics system found schemas, tables, and data parameters
• Verifiable results that can be audited by your technical team

AI for data analytics is still a growing field, and while automated insights are already helping businesses like yours take major leaps forward, baking this kind of audit trail in is vital. It removes all ambiguity, so you get all the speed of that automation with verified security.

See data in context, long-term

Every single business operates with its own unique set of quirks, internal goals, and custom tracking metrics. A generic, one-size-fits-all reporting platform can't understand the specific logic your team uses to manage inventory or classify leads.

This is why we’ve built our modern automated insights engine with persistent memory. As long as you’re conversing with your data, you can teach the assistant about the unique context in which your business operates. You can take the time to explain the specific hacks you use to categorise old stock, or define what really constitutes a ‘high-value’ lead for your sales team.

The exciting thing is that the system stores these context clues and builds on them long-term, so every future insight you receive via your AI business analytics system takes into account how your business functions. That’s data at its most applicable, so changes can be their most implementable.