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Do you trust your data? How to become a data driven company

Are you a Data Driven company? If your answer is yes, then congratulations because this means you’re able to rely on data analysis to make strategic and automated decisions, identify new business opportunities and predict future trends.
These results certainly make the difference when looking at your competitive growth. It is important to know that when a company is ready to take the leap and adapt to a Data Driven model, it needs to be done skillfully. If not, you could find yourself trapped with inaccurate, manipulated and distorted data. Let’s find out how to avoid this danger, ensuring Data Integrity and Data Intelligence in the company.

 

Data Integrity, an indispensable requirement for Data Driven companies

In addition to having a solid data analysis system in place, it’s essential to ensure the integrity of the data, i.e. its quality, accuracy and consistency.

  • The verification of the origin and life cycle of the data.
  • The adoption of measures for the protection and maintenance of data through Cyber ​​Security and Data Science tools, so as to avoid manipulation. Data Security, which refers to the protection of data from unauthorized access, is a necessary process to guarantee the integrity of the data collected.

Maintaining Data Integrity is important for several reasons. First of all, data integrity guarantees recoverability and research, traceability from its origins, and connectivity. The protection of data validity and accuracy also increases stability and performance, while improving reusability and maintainability.
By respecting the integrity requirements, it’s possible to utilize the same data for different objectives and not be limited to the purpose for which it is collected. Here is a concrete example.

 

Analyze the same data for multiple objectives: example of Retailers and Receipts

A practical example of how multiple objectives are often underestimated in the analysis of data is provided by the receipt in the Retail sector. The receipt is primarily used for fiscal needs, but in fact, the receipt also gives an aggregate of a wide range of information that can be transformed into knowledge and then into value. Starting from this, a real Data Driven company is in fact able to:

  • Identify the time of purchase and period in the year.
  • Detailed list of items purchased.
  • Calculate the average amount of the receipt and compare it to other branch shops.
  • Geolocate sales of certain products.

From the analysis of this type of data, different strategies can be created to:

 

Data Intelligence, the process that ensures maximum Data Value

A company that aims to be Data Driven must implement a Data Intelligence process that, in addition to assessing the accuracy of the data by applying standards for the origin, context and integrity, generates the maximum value from them and builds a solid foundation for the success of future digital transformation initiatives.
Data Intelligence is the complete process that allows you to transform data into information, information into knowledge and knowledge into value. Just like Business Intelligence, Data Intelligence is a vital part of any organization’s efforts to improve the services and strategies adopted. However, the two terms are not equivalent, let’s clarify this.

 

What is the difference between Business Intelligence and Data Intelligence?

Although there are some similarities in the two terms, we need to keep their differences in the forefront. Data Intelligence focuses on data used for future activities such as investments. Business Intelligence, on the other hand, refers to the understanding and optimization of a business process and related data.
We can say that Data Intelligence is “an enriched BI” with advanced data modeling and connection analysis functions at the highest level we’ve ever seen. In the end, it is used as a decision support tool for Data Driven companies.

 

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