It is the technology behind many Business Intelligence (BI) applications. OLAP is a powerful technology for data discovery, including capabilities for limitless report viewing, complex analytical calculations, and predictive “what if” scenario (budget, forecast) planning.
According to research by LinkedIn, data science and machine learning jobs are the hottest and most in-demand career paths in the world. Data scientists hold some of the most sought-after positions in the world, and if you want to boost your business intelligence or graduate career, it’s important that you boost your resume with big data.
In the far distant past (OK, just a few years ago) prospects would balk at the idea of EPM in the Cloud. Things sure have changed: the Cloud, as a means to do everything—from data storage, to playing music, to business application hosting—is as much a part of our technology ecosystem as the phones in our hands and the laptops on our desks.
Businesses are looking to create personalized messages to retain clients and attract new customers – all of which requires concerted data management. With 78% of marketers saying that data management platforms (DMP) are embedded in the overall success of a business marketing campaign, there is no denying that this concept is gaining more attention.
FROM OUR SPONSORS
The Importance of Planning and Forecasting in BI
From PARIS Technologies
The budgeting and forecasting process for most organizations is long and tedious and occurs on an annual basis, at least. Companies try to do it more often to improve accuracy and aim to ultimately implement a procedure for continuous planning, rolling forecasts, and driver-based planning.
Unlike any other business process, budgeting and forecasting is unique because it is forward thinking. Business processes like accounting, inventory tracking, invoicing, shipping, etc. are based on actual events from the past and present.
This is a fundamental difference as it also defines how the data from these processes are managed. Essentially, actual events are captured as transactions in ERPs, supply chain systems, invoicing and accounting systems, etc., and data related to it is effectively stored in its databases. On the other hand, budgets and forecasts typically reside in spreadsheets where aggregate data is entered by several people in the organization.