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The end goal of clinical technology organizations in the US and abroad is to use modern technology to bring life-saving new treatments to fruition. Leaders in this sphere help generate the evidence and insights to help biotech, pharmaceutical, medical device, and diagnostic companies accelerate value, minimize risk, and optimize outcomes. Life sciences clients recognize that technology is the answer to inefficiencies and delays in delivering new treatments to the public.

In the exponentially growing data warehousing space, it is very important to capture, process and analyze the metadata and metrics of the jobs/queries for the purposes of auditing, tracking, performance tuning, capacity planning, etc. Historically, on-premise (on-prem) legacy data warehouse solutions have mature methods of collecting and reporting performance insights via query log reports, workload repositories etc. However all of this comes with an overhead of cost-storage & cpu.

The skyrocketing value of data has created a global supply and demand for data, data applications, and data services. This new data economy is powered by technologies that enable data access and sharing, including cloud platforms, exchanges, and marketplaces.

48 experts share how to create a project management report that keeps you on top of your projects without feeling overwhelmed.

E-commerce is the future of B2C retail, with online retailers expected to generate a total of $5.55 trillion in sales in 2022. The benefits of e-commerce are almost endless: This business model overcomes geographical limitations, allows merchants to sell new products and services 24 hours a day, and eliminates many of the costs associated with managing a brick-and-mortar store. But do you know how e-commerce influences B2B analytics?

Since I joined Snowflake, I have been asked multiple times what data warehouse modeling approach Snowflake best supports. Well, the cool thing is that Snowflake supports multiple data modeling approaches equally. Turns out we have a few customers who have existing data warehouses built using a particular approach known as the Data Vault modeling approach, and they have decided to move into Snowflake. So the conversation often goes like this.

Data visualization is a core element and key capability of embedded analytics. Embedded data visualization tools create real-time visualizations (charts, graphs, etc) and can be embedded into any software application or integrated into a cloud or standalone app, and provides every user quick and easy ways to visualize information. This article explores the benefits of using embedded data visualization tools in your applications, and discusses how it can improve upon the traditional analytics experience.

To be effective, solo data analysts or engineers need to focus on refining algorithms and analyzing data, not building data pipelines.