Think back just a few years ago when most enterprises were either planning or just getting started on their cloud journeys. The pandemic hit and, virtually overnight, the need to radically change ways of working pushed those cloud journeys into overdrive. Cost-effective adaptability was essential. And the companies that could scale up or scale down quickly were the ones that navigated the pandemic successfully. Migrating to the cloud made that possible.

Microsoft recently introduced a comprehensive analytics solution for its enterprise customers, Microsoft Fabric. The solution offers data movement, data science, real-time analytics, and business intelligence within a single platform. Microsoft Fabric offers a unified platform for data engineering, science, and analytics, integrating data from Power BI, Azure Synapse, and Azure Data Factory, and using open storage for accessibility and portability.

You can now access Gemini 1.0 Pro from inside the BigQuery console, gaining scale and efficiency to ground LLMs with your business data.

In February, Snowflake released a slew of new features that continue to expand the scope of what you’re able to do with Snowflake, including the public preview of Hybrid Tables. Read on to learn more about everything we announced last month.

Tech debt is the cost of choosing quick solutions over better ones, requiring future rework. It is a fact of life for developers–when work piles up and deadlines approach, you prioritize what’s most important. In the short term, taking the easy road keeps your release schedule on track and your applications running smoothly, at least on the surface.

Achieving product-led growth (PLG) is a continuous goal for independent software vendors (ISVs) and enterprises aiming to scale efficiently and sustainably. The challenge is differentiating your product enough in a crowded market to retain users, and unlock new revenue streams. Traditional approaches to product-led growth often fall short in meeting the dynamic needs of today's data-driven users, who seek immediate, actionable insights within the applications they use.

It's summer of 1997, and I’m seven years old. I’ve just finished typing up my last homework assignment of the year, and a few loud keyboard taps later, it’s saved to a floppy disk, ready for printing at the school library. I grab my headphones and press play on my Walkman: Fleetwood Mac – Rumors.

Making sense of the ever-growing mountains of data is a challenge that organizations of all sizes face today. This article explores the powerful synergy between data warehousing and business intelligence, demonstrating how they work hand-in-hand to transform raw data into actionable insights. We’ll also delve into the role of APIs in facilitating real-time data integration and automation. Here are the key things to know about data warehousing and business intelligence: Table of Contents.

Geospatial data can give a business a competitive edge — especially when it’s combined with the company’s own data resources. Considering a new store location? You’ll want to analyze not just where your nearest competitors and potential customers are, but also retail footfall numbers, historical traffic patterns, distance from distribution centers, environmental factors, potential delivery times to customers and more. You need geospatial data to make it all happen.

Last year, we held our first Accelerate event, to explore industry trends, data and technology innovations, and data strategy case studies in financial services. This year, we are expanding to five industry events, featuring leaders in financial services; retail and consumer goods; manufacturing; media, advertising and entertainment; and healthcare and life sciences. Accelerate Financial Services and Accelerate Retail are one-day virtual events brought to you by Microsoft.