How to Efficiently Build Today’s Modern Data-Driven Applications. Data scientists need tools that give them access to previously siloed data, eliminate time wasted on data searches, increase cooperation, and reduce bottlenecks. Find out what makes Snowflake unique thanks to an architecture and technology that enables today's data-driven organizations.
Data scientists need tools that give them access to previously siloed data, eliminate time wasted on data searches, increase cooperation, and reduce bottlenecks.
A robust data pipeline is at the heart of modern data solutions. Whether it is training or inference, any enterprise-level AI model must become part of the data analytics pipeline for production deployment. And the integration of the model into the data pipeline must be able to work in multiple deployment models.
Data scientists may start with simple prototyping, but working with enterprise boundaries requires scale. Operationalization is complicated, causing the bottleneck and eventual death of AI deployment in all but the most straightforward cases. That is not a scenario most companies can withstand. Increasingly, AI is viewed as a competitive differentiator that will allow one company to succeed versus another.
So, what do companies do? Businesses that manage to build modern data-driven applications will survive. Here’s how a business can work to build that elusive production-grade, enterprise-ready, end-to-end solution to harness real data.
One problem when developing and deploying AI within a business is that there are different data criteria for different pipeline and deployment stages. Ensuring the right data is used, is in the correct format, and properly secured at each step in a data pipeline or analysis workflow are time-consuming tasks. These tasks divert data scientists away from their main objective of turning data into insights.
In this article, see the role of big data in healthcare and look at the new healthcare dynamics. Big Data is creating a revolution in healthcare, providing better outcomes while eliminating fraud and abuse, which contributes to a large percentage of healthcare costs.
‘Data is the new science. Big Data holds the key answers’ - Pat Gelsinger The biggest advantage that the enhancement of modern technology has brought
We need no rocket science in understanding that every business, irrespective of their size in the modern-day business world, needs data insights for its expansion. Big data analytics is essential when it comes to understanding the needs and wants of a significant section of the audience.
A lightweight desktop script tool is a must-have for data analysts. But how do you know which is the most suitable one?
A data expert discusses the three different types of data lakes and how data lakes can be used with data sets not considered 'big data.'