Business Intelligence (BI)
Online Analytical Processing
Online Analytical Processing (OLAP) analyzes business information in a multidimensional way to aid in complex calculations, trend analysis, and data modeling. OLAP gives the applicant the ability to analyze specific data in multiple dimensions to gain the necessary insight to make a decision.
Companies are constantly bringing information together to perform various analyses. They have a strong need to get all the data in one place to get an accurate and reliable understanding of different aspects of the data. OLAP can help them do that: quickly access multidimensional analysis results.
What makes OLAP different from other analytics tools is its ability to store information in a multidimensional database structure. Dimensions to use are, for example, locations, timeframe, personnel, products, accounts, etc.
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Corporate Performance Management
Corporate Performance Management (CPM) includes methods, metrics, activities, and systems used to monitor and manage a company's business performance. CPM processes the targeted information to convert it into operational plans.
This process and methodology provides companies with an integrated approach to planning, forecasting for finance, sales, marketing, HR and operations. When implemented, this methodology connects business strategies with plans and executions, enabling a business to succeed and improve.
CPM is an important part of business intelligence for companies looking for changes such as budget reform, cost savings, upgrading organizational strategy, fine-tuning KPIs and improving the financial planning process for example, etc.
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Real-time Business Intelligence
Real-time business intelligence (RTBI) is used to sort and analyze business data and operations that are done with directly insightful data.
RTBI enables a company to gain real-time insight into the business process in order to make strategic decisions or immediately execute a course of action. This can be used when making business decisions when it comes to, for example, calculating the most suitable moment, the best profit realization, the expected result, etc.
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Data warehousing (DWH) helps create important metrics about the current market or company. DWH means that huge amounts of data are stored in many special ways, which can be useful for analysis.
DHW receives updates from data from apps and systems that can be used by the company. The data is formatted and synchronized to match the data already stored in the warehouse. The processed data becomes readily available to the applicant to help them make business decisions.
DHW is different from a simple database. Data warehouses are created to perform an analysis of a large amount of data. In the shortest possible time, the goal is to receive, process, present, etc.
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Data Sources (DS) are important in retrieving raw data from many different sources, both internal and external, so essential for the various analytics capabilities. Operational data sources that you can take advantage of are: Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), Ecommerce Apps, Human Resource Management (HRM), etc.
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