The time required to execute an AI project can vary depending on several factors, including the complexity of the problem, the availability and quality of data, the scope of the project, and the specific requirements. Some AI projects can be completed in a matter of weeks, while others may take several months or longer. It is crucial to thoroughly analyse the project requirements, assess the data availability, and develop a comprehensive project plan to estimate the timeline accurately.

If you are facing challenges that involve processing large amounts of data, identifying complex patterns, making predictions, automating tasks, or improving decision-making based on data-driven insights, AI may be a suitable solution. Consulting with our experts can help assess your specific problem and determine if AI is the right approach to address it effectively.

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that can perform tasks, learn, and make decisions. Machine Learning (ML) is a subset of AI that focuses on enabling machines to learn and improve from data without being explicitly programmed.

This can admittedly be a tough sell, and a barrier to adoption - no matter how you try to meet the needs of your entire user base, there are some who prefer their own self-directed analysis, typically based on large Excel-like tables. The good news is that, to some degree, all modern BI platforms support the generation of CSV or Excel-based extracts, up to and including the entire data model. In that sense, BI platforms allow users to continue exploration beyond the page’s visuals so no one is, in effect, left out.

Choosing a BI platform can be difficult, since on the surface, they all achieve the same outcome.

That said, your technology stack and data ecosystem will play a significant role in your choice. If, for instance, you are a 100% Microsoft business, we’d likely recommend Power BI. If you have a large Salesforce.com user base, we’d suggest Tableau CRM.

Often enough though, enterprises cross multiple systems and methods for capturing and storing data, so the choice often comes down to which platform is the most appealing, both in terms of visual output and capabilities, and price. At The Virtual Forge, we tend to stay platform-agnostic when entering a new situation in order to find the best fit that meets the majority of your needs.

Typically, most BI platforms offer some sort of trial period to “test drive” the tool. Some, like Power BI, allow you to create and publish dashboards and reports without any additional licensing, though at some point, in order to be able to easily share and collaborate, licensing will definitely be required. Once you’ve reached that point, the level of licensing will vary depending on the size of your intended audience, as well as platform-specific considerations. 

In general, the answer is almost always “yes”, though to what extent varies by situation.

There’s always some degree of cleansing and preparation, though the scope of that effort depends on the maturity of the data in question, and the means by which it is accessed.

If, for instance, you have an established data warehouse, consuming data from multiple sources in a central location, it’s very likely that little to no preparation is necessary.

By contrast, if the sources are Excel-based and touched by many hands in the chain of control, or derived from web-based sources, then it’s very likely to require anomaly detection and resolution, and a high-degree of shaping to fit the ideal reporting data model.

While a data warehouse should be considered an integral part of any enterprise-wide analytics solution, it’s not necessarily a pre-requisite to be up and running on most BI platforms.

Modern BI solutions, to varying degrees depending on the platform, have incorporated at least some level of data pipelines, transformations, and cleansing, functions typically carried out in the traditional warehouse.

While the data warehouse is the more complete solution, these platforms are designed to get you started exploring your data quickly, which is great news for smaller businesses or teams where a full-blown warehouse isn’t financially feasible.

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A dashboard is a user-friendly interface that displays critical information and data in a visual format (bar graphs, pie charts, heat maps, scatter plots, etc.). The purpose of a dashboard is to provide quick and easy access to key metrics, data, and insights that help inform decision-making and drive business performance. Dashboards can be designed to display a wide range of data from multiple sources, including real-time updates, historical trends, and predictive analytics.

Data Dashboards become essential by providing real-time insights, improve communication, increase productivity, and enable data-driven decision-making. They can be customised to meet the specific needs of your business, providing a single source of truth for decision making.

By linking dashboards to particular metrics or KPIs, you gain critical business intelligence and the capability to delve into specific pieces of information, enabling you to continuously track your progress.

There's no one-size-fits-all answer to this question - it depends on the maturity of the data in question, and the means by which it is accessed. If, for instance, you have an established data warehouse, consuming data from multiple sources in a central location, it's very likely that little to no data preparation is necessary. By contrast, if the data sources used are Excel-based and touched by many hands in the chain of control, or derived from web-based sources, then it's very likely to require anomaly detection and resolution, and a high-degree of shaping to fit the ideal reporting data model.

Put simply, a Power BI consultant is an expert in the field with a situation-dependent, malleable role. Through years of experience on the data platform side, a Power BI consultant has acquired the knowledge to fulfill many roles: data modeler, visual designer, advisor, and trainer. Above all, a Power BI specialist has learned to listen to you, and to assume the role that best meets your needs.

Whether you're just starting out in Power BI, encountered a seemingly intractable problem, or simply need an expert to review your implementation, , and data models, Power BI experts and consulting services exist to help you meet your unique needs efficiently and with minimal investment in time and manpower.

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Fabric is the latest innovation from Microsoft, with the aim of establishing an all-in-one, tightly integrated analytics platform. It encompasses ETL pipelines, data warehousing, AI capabilities, and visualisation via Power BI in a single scalable package.

Power BI is a best-in-class analytics tool, designed to deliver an end-to-end analytics solution, from data ingestion and cleansing, to data model design, to the delivery of beautiful and informative visuals, all wrapped in an intuitive, easy-to-use package.