Remove Cost-Benefit Remove Data Warehouse Remove Marketing Remove OLAP
article thumbnail

The Ultimate Guide to Data Warehouse Automation and Tools

Jet Global

This puts tremendous stress on the teams managing data warehouses, and they struggle to keep up with the demand for increasingly advanced analytic requests. To gather and clean data from all internal systems and gain the business insights needed to make smarter decisions, businesses need to invest in data warehouse automation.

article thumbnail

Unlocking Data Storage: The Traditional Data Warehouse vs. Cloud Data Warehouse

Sisense

Data warehouse vs. databases Traditional vs. Cloud Explained Cloud data warehouses in your data stack A data-driven future powered by the cloud. We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Data warehouse vs. databases.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Database vs. Data Warehouse: What’s the Difference?

Jet Global

Whether the reporting is being done by an end user, a data science team, or an AI algorithm, the future of your business depends on your ability to use data to drive better quality for your customers at a lower cost. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise?

article thumbnail

Prevent Customer Churn: Customer Retention in the Transition to Microsoft D365 F&SCM

Jet Global

These benefits come with a caveat, however. Why not take that opportunity to look around at the offerings from SAP, Sage, Epicor, Acumatica, or any of the other leading ERP vendors on the market? In this respect, we often hear references to “switching costs” and “stickiness.” A Look at Switching Costs For ERP.

article thumbnail

How OLAP and AI can enable better business

IBM Big Data Hub

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. As AI techniques continue to evolve, innovative applications in the OLAP domain are anticipated.

OLAP 58
article thumbnail

Why Business Intelligence is Top of Mind for CFOs for 2022

Jet Global

The term “ business intelligence ” (BI) has been in common use for several decades now, referring initially to the OLAP systems that drew largely upon pre-processed information stored in data warehouses. As the cost benefit ratio of BI has become more and more attractive, the pace of global business has also accelerated.

article thumbnail

Data Mining – useful or not?

Jen Stirrup

This model can assist in decision making and in focusing marketing efforts. One particular technology which is good for summarising and aggregating data is called OLAP (On Line Analytical Processing). Historical and predictive analytics are not mutually exclusive, but instead work together to inform the marketing process.