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
Online Analytical Processing (OLAP) is crucial in modern data-driven apps, acting as an abstraction layer connecting raw data to users for efficient analysis. It organizes data into user-friendly structures, aligning with shared business definitions, ensuring users can analyze data with ease despite changes.
While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.
Each data entity provides an abstract representation of businessobjects within the database, such as, customers, general ledger accounts, or purchase orders. Online analytical processing (OLAP), which enabled users to quickly and easily view data along different dimensions, was coming of age. Data Lakes.
With all the attention being paid to artificial intelligence (AI) these days, it’s no surprise that enterprise leaders are scrambling to find ways to shoehorn AI implementations into their technology stack. What are some of the core components of business intelligence? The post AI vs. BI for Business, What Do You Need?
While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.
Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization.
Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization.
For users of Oracle E-Business Suite (EBS), data access is about to get a bit more difficult now that the company has phased out the Oracle Discoverer product. As a heavyweight in the world on enterprise software, Oracle makes a lot of companies scramble any time it decides to stop supporting one of its core products. What Comes Next?
Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.
The data warehouse is highly business critical with minimal allowable downtime. For an example, refer to How JPMorgan Chase built a data mesh architecture to drive significant value to enhance their enterprise data platform. He specializes in migrating enterprise data warehouses to AWS Modern Data Architecture.
Improving security with SOC 2, SSO, and RBAC Critical enterprise security features can be challenging to implement in open source Pinot environments. StarTree Cloud provides enterprise-grade security with SOC 2 compliance, enhanced encryption, and single sign-on (SSO) capabilities.
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