Business data refers to the information about people, places, things, business rules, and events in relation to operating a business.
Serious businesses need to consider setting up business intelligence and data warehouses. In pursuing these capabilities, they need to adopt a holistic view coupled with wise investment and careful execution. For a business to really grow, it should consider interrelated areas involving people, strategy, process, applications, metrics, data and architecture.
It is very important to gather business data and base an organization’s decision on the statistical report to get precise decisions on how to more the company forward for sustainability.
Knowing things about people and their buying behaviors can make a company generate very important business data. For instance, statisticians and market researches know that certain age groups have unique buying habits. Races and people from different demographics locations also have buying patterns of their own so gathering these information in one business database can be a good way to future target marketing.
In terms of production, business data about where to get raw materials, how much the cost is, what are the customs and importation policies of the raw materials’ country of origin and other information are also very important.
There are many software applications that manage business data for easy statistical reporting and spotting of trends and patterns.
The Business Data Catalog functionality in some applications allows users to present line-of-business data. It can search and retrieve information from back end systems such as Enterprise Resource Planning (ERP), Customer Resource Management (CRM), Advance Planner and Optimizer (APO) and Supply Chain Management (SCM).
In many companies, they maintain a business data warehouse where data from several are collected and integrate every few minutes. These repositories of business data may supply needed information to generate reports and recommendations in an intelligent manner. Hence the term Business Intelligence is already widely used in the business industry today.
Business intelligence generally refers to technologies and software applications that are used to gather, integrate and analyze business data and other information pertaining to the operation of the company. It can help companies gain more comprehensive and in depth knowledge of the many factors that can affect their business. These knowledge may include metrics on sales, internal operations and production. With recommendations from business intelligence, companies can make better decisions for the business.
For processing billions of business data in the data warehouse for business intelligence, companies use high powered and secure computer systems that are installed with different levels of security access.
Several software applications and tools have been developed to gather and analyze large amounts of unstructured business data ranging from sales statistics, production metrics to employee attendance and customer relations. Business intelligence software applications very depending on the vendor but the common attribute in most of them is that they can be customized based on the needs and requirements of the business company. Many companies have in-house developers to take care of business data as the company continues to evolve.
Some example of business intelligence tools to process business data include Score carding, Business activity monitoring, Business Performance Management and Performance Measurement, Enterprise Management systems and Supply Chain Management/Demand Chain Management. Free Business Intelligence and open source products include Pentaho, RapidMiner, SpagoBI and Palo, an OLAP database.
Business data is the core of the science of Analytics. Analytics is the study of business data that uses statistical analysis in knowing and understanding patterns and trends in order to foresee or predict business performance. Analytics is commonly associated with data mining and statistical analysis although it is more leaned towards physics-like modeling which involves extensive computation.