It is no news that organizations generate a large amount of data that, in turn, must be interpreted.
To do this, there are some tools such as business analytics that are dedicated to analyzing this information and translating it.
Through this methodology, companies not only make business decisions, but also automate and optimize organizational processes to gain a competitive advantage.
Now, business analytics combines a series of elements that you should know before implementing. In this article we tell you everything you need to know to use this powerful tool in your company.
Essential elements in business analytics
Before putting business analytics into practice, we first need to understand its concept and the elements that compose it.
Business analytics is the process of using quantitative methods to derive meaning from data. By understanding information, businesses can make informed and sound decisions.
Companies use data as a corporate asset and leverage it to gain competitive advantage . In an organization, data enables:
Within the entire information analysis process, business analytics considers the following elements:
Customer
Observing our current and list of telegram users in laos potential clients helps us detect new trends and respond to them in time.
In this sense, business analytics, through data collection, allows for the development of strategies that improve customer experience .
With this, you will be able to know your consumer better and strengthen your relationship with them, which will contribute to their loyalty .
Technology
technology-analytics-business-analytics
Digitizing strategic processes in the company is essential to increase competitiveness. In addition, it is a key element when seeking to optimize team functions and increase their productivity .
Define which areas of your company need to implement or update technology. Invest in tools that really add value and in systems that adapt to your processes and not the processes to the system.
Recruiting a specialized team
Efficient management of large volumes of information requires specialized talent in data science.
Therefore, it is not only necessary to recruit profiles with technical skills in Big Data Analytics. Talent must also have business vision, creativity and skills to lead or coordinate teams.
Data Infrastructure
A good data infrastructure enables efficient access to company information and provides insights that help quickly deliver solutions to the organization's needs.
You can hire a software service , develop it internally with a specialized team , or opt for a free one. The important thing is that the software allows you to collect, analyze, compress, and organize data with high performance.
The data infrastructure must include:
Architectures: Corresponds to the way in which the database is stored.
Sources: Refers to information obtained from both internal and external sources of the organization about customers, products and services; as well as customers and social networks, among others.
Analysis and modeling: It is the processing of data to validate, standardize and integrate it into a common source.
Exploration and visualization: In this phase, the data architecture, sources, and modeling are defined. This means that data can be explored and visualized using tools such as dashboards and key performance indicators ; this allows for easy information extraction and efficient decision making.