This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. Thankfully, with widespread adoption of cloud computing and the Internet of Things, data has never been more readily available in today’s business world.
Thankfully, with the widespread adoption of cloud computing and the Internet of Things, data has never been more readily available in today’s business world. Cubes are multi-dimensional datasets that are optimized for analyticalprocessing applications such as AI or BI solutions.
Consumption This pillar consists of various consumption channels for enterprise analytical needs. It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers.
Trace the flow of data from its origins in the source systems, through the data warehouse, and ultimately to its consumption by reporting, analytics, and other downstream processes. Data model design – Review the data model and table design and provide recommendations for sort and distribution keys, keeping in mind best practices.
Thankfully, with the widespread adoption of cloud computing and the Internet of Things, data has never been more readily available in today’s business world. Cubes are multi-dimensional datasets that are optimized for analyticalprocessing applications such as AI or BI solutions.
We organize all of the trending information in your field so you don't have to. Join 42,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content