The data platform for the era of AI
Your organisation recognises that having timely data insights to guide informed business decisions is pivotal to your success.
Yet making the correct data available that enables detailed drill-downs, when and where people are making decisions remains a challenge for many.
Your most valuable data often comes from cross-referencing data from different systems. For example, CRM data with ERP data, operations, HR, project management, case management, or scheduling systems. Siloed data across different systems is often complex to combine. The need for data governance plays a critical role here as it helps establish policies and standards for data quality, security, and compliance.
As a result, teams and departments are burdened with disparate data sources, escalating licensing costs and an overcomplicated matrix of analytics tools.
This scenario leads to knowledge loss and challenges in retaining information amidst staff turnover, resulting in a steep learning curve for new employees who must master various analytics tools.
As the volume of essential data for analysis increases daily, the need for a simple solution that brings data together coherently becomes critical.
Microsoft Fabric is an all-encompassing analytics solution for enterprises. It integrates services like data integration, data engineering, data storage, data science, real time analytics, data visualisations, data governance, and AI solutions that work together by design.
Built on a Software as a Service (SaaS) foundation, it brings together tools like Power BI, Azure Synapse, and Azure Data Factory, offering a unified platform for data analytics.
Fabric also includes a unified data storage system called OneLake. Think of OneLake as the OneDrive of data; just as OneDrive consolidates all your files into one
location, OneLake does the same for all your data.
Fabric is a comprehensive solution for all your data analytics needs, reducing the complexity of managing multiple systems or vendors and potentially lowering infrastructure costs related to data analytics.