Using AI for Enhanced Workflows in Pyramid Analytics

Business intelligence involves a lot of grunt work before you get to the interesting part. AI can take over those tedious steps across the board by creating enhanced workflows that leverage powerful tech.  

Most businesses today use AI in at least one function, and for good reason. It can handle data prep, semantic definitions, automate recurring processes, and extend analytics access to line-of-business decision makers. Whether or not they’re using AI to help, many teams tackle these aspects of data analytics on a piecemeal basis.

Pyramid Analytics has built its decision intelligence platform to bring all of these capabilities together in one place, allowing organizations to move from scattered tools to a unified system that works end-to-end. The platform not only brings AI capabilities to your fingertips but also makes the process more intuitive for everyone involved.

Here are a few of the ways Pyramid Analytics is making AI workflows more efficient and accessible for everyone involved in BI.

AI-Accelerated Data Preparation

Data preparation once meant writing endless scripts or waiting for someone else to clean your datasets. Pyramid Analytics changes that with tools that let you build data flows visually, with no coding required. You drag components into place, connect to your sources through prebuilt integrations, and watch the pipeline take shape. 

The AI layer quietly runs in the background, spotting inconsistencies in your data and suggesting ways to align schemas that don’t quite match. It also handles metadata assignments that would normally take hours of manual work.

Data engineers get the governance controls they need to maintain quality standards across the organization. Analysts can build reusable pipelines that teams trust. Strategists who know the business context best can create their own flows without filing IT tickets and waiting days for responses.

What’s more, everything lives in one environment, so when you update your prep logic or refine a semantic model, those changes flow through to every dashboard and analysis model automatically. No broken connections, no version mismatches, no wondering if reports reflect the latest definitions.

AI-Powered Analytics and Smart Insights

Instead of just displaying your data, the platform actively looks for patterns you might miss. Basically, Pyramid’s AI engine safely answers your natural questions about connected datasets, surfacing insights automatically, pointing out trends, projections and anomalies that deserve attention and drilling down into key drivers behind trends. 

Instead of staring at a chart trying to figure out what story it tells, the system generates natural language explanations that translate complex visualizations into plain sentences anyone can understand. It suggests analyses you hadn’t considered, fills in gaps where context is missing, and refines visualizations that make sense for the data type you’re working with.

Using these capabilities, stakeholders can deliver trustworthy, explainable insights at scale, without poring over individual summaries for every analysis. Managers and executives get context they can read and act on immediately, no technical background required. Business analysts spend less time explaining charts and more time exploring what the numbers mean for strategy.

Because it’s all managed under one platform, the AI that recommends visualizations and generates narratives draws from the same metrics management layer that powers your data prep and modeling work. Everyone sees consistent definitions and calculations, so you avoid the confusion that happens when different tools produce different versions of the same metric.

Integrated Data Science

Many organizations treat data science as something separate from business analytics, which creates friction when you try to put insights into action. Pyramid brings the data science workbench directly into the decision intelligence platform, giving you advanced modeling and predictive capabilities right where you already work. 

The platform supports selecting whichever AI model might work best for your use case, saving you from trial and error with dozens of algorithms. You can run your data science processes at the prep layer rather than waiting until data flows downstream. This way, predictions and classifications occur earlier in the pipeline when they’re most useful.

Data scientists can move models from prototype to production faster, because the infrastructure already exists. Analysts who understand the business but haven’t studied machine learning can still build predictive insights using guided workflows. Teams that need forecasts or classifications get access without hiring specialized talent.

Logic models live in the same environment where data is prepared, and dashboards get published, so governance policies apply consistently across projects. You can track how model outputs impact business decisions over time. You won’t need to stitch together separate systems or worry about discrepancies between production and development models.

Conversational Analytics With Governed GenAI

Asking questions about your data shouldn’t require learning query languages or bothering the analytics team every time you need an answer. Pyramid lets anyone type or speak questions in any language and get back actual insights, not error messages. 

Embedded analytics capabilities let these conversational tools appear wherever your team actually works, whether that’s in a custom application, a portal, or a workflow tool.

The conversational interface understands business terms because it runs on top of your governed metrics and business logic, so “revenue” means the same thing whether you’re chatting with the bot or talking to a coworker from a different business unit. This setup also enables you to enrich your internal datasets with external information, such as population statistics, weather patterns or economic indicators, without leaving the system.

Business users and domain experts get direct access to data without writing SQL or waiting for reports. Power users can prototype analyses faster by generating strategy logic models on the fly.

The embeddable natural language interface features operate on centrally governed data with consistent security and semantic definitions. You get flexible exploration without the risks that come from bolting chat tools onto ungoverned data sources where definitions vary, and access controls get murky.

Intelligence That Travels With Your Data

Most platforms ask you to choose between power and simplicity, technical depth and business accessibility. Pyramid removes that tradeoff by embedding AI capabilities throughout the entire analytics lifecycle. Data scientists, engineers, analysts, and business users all work in the same environment with tools matched to their needs. 

Governance travels with the data automatically, so opening up access doesn’t mean losing oversight. The platform grows with your team’s skills instead of forcing everyone into rigid roles. Organizations get the sophisticated capabilities they need without the fragmentation that usually comes with enterprise analytics stacks.